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Master of Science Thesis
KTH School of Industrial Engineering and Management
Energy Technology EGI-2016-097 MSC
Division of Applied Thermodynamics and Refrigeration
SE-100 44 STOCKHOLM
Natural ventilation strategies for
nearly-Zero Energy Sports Halls
Alessia Accili
Master of Science Thesis
KTH School of Industrial Engineering and Management
Energy Technology EGI-2016-097 MSC
Division of Applied Thermodynamics and Refrigeration
SE-100 44 STOCKHOLM
Master of Science Thesis EGI 2016:097 MSC
Natural ventilation strategies for nearly –
Zero Energy Sports Halls
Alessia Accili
Approved
6th of October 2016
Examiner
Jaime Arias Hurtado
Supervisor
Jaime Arias Hurtado
Commissioner
Contact person
Abstract
In line with the article 9 of the EPDB, member states shall ensure that all new public properties are nearly
zero energy buildings (n-ZEB) by December 31, 2018. Sports buildings account for a significant share of
the European building stock consumption. More than half of their current energy needs are related to
lighting, and a relevant energy use is due to domestic hot water. This work aims to test different energy
measures to design nearly zero energy sports halls in Mediterranean climates. Under a holistic approach,
the design of the base case sports hall includes the implementation of passive strategies in combination
with renewable energy and energy efficient systems in order to meet the n-ZEB conditions. However, a
special focus is put on the study of the sports hall ventilation requirements. A natural ventilation system is
proposed as an alternative to a traditional mechanical one. The effectiveness of the analyzed ventilation
strategies is validated using TRNSYS, a dynamic simulation tool. Therefore, natural ventilation impact on
thermal comfort, air quality and energy needs is estimated. A cost effective evaluation is done following
the methodology proposed by the European Directive. Additionally, the study is complemented with a
short period of measurements in a selected existing facility according to which poor indoor air quality is
the main cause of users discomfort during period of maximum occupancy. The obtained results show that
the combination of reduction of thermal transmittance of the envelope, optimization of the windows
surfaces, façades orientation, introduction of shading devices, installation of energy efficiency systems as
LED lamps and use of natural and night ventilation, are advantageous for the reduction of heating,
cooling and artificial lighting demand. Overall, consisted primary energy savings are achieved. Moreover,
the described strategies ensure indoor thermal comfort, minimizing the period of overcooling and
overheating, and provide good air quality conditions for most of the occupied time along one year
simulation. Finally, it is verified that the PV system integration positively affects the sports hall
performance toward n-ZEB standards.
iii
Sammanfattning
EUs direktiv om byggnaders energiprestanda (EPBD - 2002/91/EC) uppdaterades 2010 och har som mål
att minska energianvändning i Europas fastighetsbestånd. Efter den 31 december 2018, ska alla nya
byggnader som används av offentliga myndigheter vara nära-nollenergibyggnader.
Idrottshallar står för en betydande andel av den totala energianvändningen i EU. Denna rapport syftar till
att studera olika energieffektiviseringsåtgärder, förnybara energikällor och passiva strategier för att utforma
n-ZEB idrottshallar i medelhavsklimat.
Ett särskilt fokus läggs på att studera ventilationskraven i idrottshallar och användning av naturlig
ventilation. Energiprestanda av de analyserade ventilation strategierna har studerats i programmet
TRNSYS som är ett verktyg för dynamisk simulering av byggnader. Under projektet har mätningar
genomförts i en idrottshall i Barcelona för att analysera de olika parametrarna som påverkar
energianvändning i dessa byggnader.
En ekonomisk analys att de olika energieffektiviseringsåtgärderna har utförts.
Resultaten från projektet visar att lämplig naturlig ventilation i idrottshallar, kan säkerställa god luftkvalitet
inomhus och termisk komfort. Dessutom kan naturlig ventilation minska energianvändningen och de
totala kostnaderna.
iv
Acknowledgment
My deepest gratitude goes to my supervisors in IREC, Dr. Jaume Salom and Joana Ortiz for their constant
support and guidance in all phases of the realization of this project.
I would like also to thank all the Thermal Energy and Building Performance Group of IREC. I have
learned an incredible amount of valuable skills in the last six months spent with you.
Fins ara!
v
Nomenclature
Abbreviations
Abbreviation Meaning
BBCC Bioclimatic Chart
BIPV PV Building Integration
BMS Building Management System
CB Condensing Boiler
CEC5 Central Europe Cooperation programme
CTE Código Técnico de la Edificación
CFD Computation Fluid Dynamics
DHW Domestic Hot Water
DVC Demand Controlled Ventilation
EPBD Energy Performance of Buildings Directive
EPC Energy Performance Coefficient
EU European Union
HP Heat Pump
HVAC Heating Ventilation and Air Conditioning
IAQ Indoor Air Quality
ICAEN Institut Catala d’Energia
IEQ Indoor Environmental Quality
IREC Catalonia Institute for Energy Research
MS Member State
MV Mechanical ventilation without control strategy
MV + DV Mechanical ventilation with variable speed fan
MV +CTL Mechanical ventilation with control strategy
NPL Neutral Pressure Level
NPV Net Present Value
NV Natural Ventilation
n-ZEB Nearly Zero Energy Building
PAV3 Triple sports hall
PMV Predicted Mean Vote
PPD Predicted Percentage of Dissatisfied
SBS Sick Building Syndrome
vi
Symbols
Symbol Unit Meaning
m kg/h Net mass flow
Q kJ/h Heating rate
∆P Pa Pressure difference
A m2 Area
ACH h-1 Air Change Rate
Ar/ADU - Skin portion involved in the radiative heat exchange
C W/m2 Rate of convective heat loss
C+R W/m2 Sensible heat loss from skin
Cd - Discharge coefficient
CLO clo Clothing insulation
Cp - Static pressure coefficient
cp KJ/kgK Specific heat
Cs kg/s Air mass flow coefficient
DLE minutes Duration Limited Exposure
Dmax Wh/m2 Maximum value of water loss
E W/m2 Rate of convective heat loss
Ereq W/m2 Required Evaportation Rate
fcl - Ratio of clothed surface area to nude surface area
FLNEL kg/h Net mass flow per link (TRNFLOW output)
g m/s2 Gravitational acceleration
g-value (T-SET) - Total Solar Energy Transmittance
H m High difference
h W/m2K Heat transfer coefficient
K - Flow coefficient
M W/m2 Rate of metabolic heat production
MET met Metabolic activity
n - Flow exponent
N rpm Fan speed
n50 h-1 External envelope airtightness. Air permeability at 50 Pascal.
p Pa Pressure
P W Power
pa Pa Partial water vapor pressure
vii
Q m3/s Flow rate
Qmax Wh/m2 Maximum value of body heat storage
R % Market Interest Rate
RD % Discount Rate
RE - Energy Evolution Rate
RI % Inflation Rate
RR - Real Interest Rate
RXE - Energy Cost Evolution
S W/m2 Rate of heat storage
SWreq W/m2 Required Sweat Rate
T or t or ϴ °C or K Temperature
U W/m2K Thermal transmittance
V or v m/s Velocity
Vol m3 Volume
W W/m2 Rate of metabolic work accomplished
Wmax - Skin weatness
z m High
α - Wind velocity profile exponent
ρ kg/m3 Density
viii
Subscripts
Subscript Description
0 standard condition for dry air
a or air air
c convective
cl clothing
cr core
da daily average
ea exponential average
ext exterior
f final energy
g globe
hr hour
int interior
m mean
max maximum
min minimum
NW North-West
op operative
opt optimal
out exterior
p primary energy
r radiant
ref reference
res respiration
s static
SE South-East
sk skin
w wind
ix
Table of Contents
Abstract ........................................................................................................................................................................... ii
Sammanfattning ............................................................................................................................................................ iii
Acknowledgment .......................................................................................................................................................... iv
Nomenclature................................................................................................................................................................. v
Abbreviations ............................................................................................................................................................ v
Symbols ..................................................................................................................................................................... vi
Subscripts ................................................................................................................................................................viii
List of figures ................................................................................................................................................................ xi
List of tables ................................................................................................................................................................ xiii
1 Introduction .......................................................................................................................................................... 1
1.1 Scope ............................................................................................................................................................. 2
1.2 Report structure........................................................................................................................................... 2
2 State of the art ....................................................................................................................................................... 4
2.1 Sports Hall energy consumption .............................................................................................................. 4
2.2 Nearly Zero Energy Sports Halls ............................................................................................................. 5
3 Theoretical framework ......................................................................................................................................17
3.1 Natural ventilation ....................................................................................................................................17
3.1.1 Natural ventilation driving forces ..................................................................................................17
3.1.2 Natural ventilation strategies ..........................................................................................................18
3.1.3 Natural ventilation technical solutions .........................................................................................20
3.2 Thermal comfort .......................................................................................................................................23
3.2.1 Predicted mean vote ........................................................................................................................23
3.2.2 Adaptive model ................................................................................................................................26
3.2.3 Required sweat rate ..........................................................................................................................29
3.2.4 Givoni diagram .................................................................................................................................30
3.3 Indoor Air quality......................................................................................................................................30
4 Methodology .......................................................................................................................................................32
5 Measurement campaign .....................................................................................................................................33
5.1 Assumptions and parameters ..................................................................................................................35
5.2 Data elaboration ........................................................................................................................................37
6 Proposed n-ZEB strategies ...............................................................................................................................40
7 Base case description .........................................................................................................................................41
7.1 The triple sports hall .................................................................................................................................41
7.2 Occupation patterns .................................................................................................................................43
7.3 Weather data ..............................................................................................................................................43
7.4 3D geometry definition ............................................................................................................................45
x
8 TRNSYS: building simulation ..........................................................................................................................46
8.1 Thermal behavior ......................................................................................................................................46
8.2 Internal gains ..............................................................................................................................................48
8.3 Natural ventilation ....................................................................................................................................49
8.3.1 Control strategy ................................................................................................................................51
8.4 Mechanical ventilation ..............................................................................................................................53
9 PV system design ................................................................................................................................................56
10 Cost-optimality methodology ...........................................................................................................................58
10.1 Calculation hypothesis ..............................................................................................................................59
11 Results and discussion .......................................................................................................................................62
11.1 Measurement campaign............................................................................................................................62
11.1.1 Survey results ....................................................................................................................................62
11.1.2 Thermal comfort analysis ...............................................................................................................64
11.1.3 Air quality: indoor CO2 concentration .........................................................................................70
11.2 Ventilation strategies ................................................................................................................................72
11.2.1 Natural ventilation results ...............................................................................................................72
11.2.2 Mechanical ventilation results ........................................................................................................76
11.2.3 Energy consumption comparison .................................................................................................76
11.3 PV system configurations ........................................................................................................................78
11.4 Energy balance of n-ZEB strategy .........................................................................................................79
11.5 Cost-optimal evaluation ...........................................................................................................................80
Conclusion ....................................................................................................................................................................85
Publication ....................................................................................................................................................................86
Bibliography .................................................................................................................................................................87
Annex 1 .........................................................................................................................................................................96
Annex 2 .........................................................................................................................................................................97
Annex 3 .........................................................................................................................................................................99
Annex 4 ...................................................................................................................................................................... 100
Annex 5 ...................................................................................................................................................................... 101
xi
List of figures
Figure 1. Analysis of primary energy consumption share per building category at country level. Source:
Aelenei et al. (2015) ....................................................................................................................................................... 4
Figure 2. Catalan Sports Hall primary energy consumption (kWh/m2). Heating includes ventilation.
Source: self-elaboration based on data ICAEN (2012) ........................................................................................... 5
Figure 3. Summer ventilation. Night ventilation: the fresh air enters on the basement and goes out from
the top openings. Source: Flourentzou et al. (2015) ................................................................................................ 8
Figure 4. Sports Hall in Commune de Savièse in Switzerland. Source: Flourentzou et al. (2015) ................... 8
Figure 5. Winter ventilation. Air enters from the top lateral openings and goes out from the top front
opening in order to avoid cold draughts. Source: Flourentzou et al. (2015) ....................................................... 8
Figure 6. Energy efficiency strategies implemented in the Sports Hall of Nanyang Technological
University in Singapore. Source: The Singapore Engeneering (2015) ................................................................10
Figure 7. Chilled water coils, at a high level, used to cool down warm air. Source: The Singapore
Engeneering (2015) .....................................................................................................................................................10
Figure 8. Summer ventilation in the Passive Sports Hall of Slomniki. Source: CEC5 (2014) ........................11
Figure 9. Building features of the Sports Hall in Unterschleißheim. Source: SEAI (2010).............................13
Figure 10. Sports Hall in Loch. Source: BEHNISCH ARCHITEKTEN (2015) .............................................14
Figure 11. Left: the wind cap. Right: interior view of the solar chimney. Source: Reijenga (2005) ...............15
Figure 12. Ventilation tower: summer ventilation (left); winter ventilation (right). Source: Reijenga (2005)
........................................................................................................................................................................................15
Figure 13. Schematic of mixed local/global and stack/wind ventilation strategy. Source: Axley (2001) .....19
Figure 14. Window opening types. Source: Roetzel et al. (2010) ........................................................................22
Figure 15. Relationship PMV versus PPD. Source: Djongyang et al. (2010) ....................................................25
Figure 16. Thermal adaptive process. The components of adaptation to indoor climate. Source: de Dear et
al. (1997) ........................................................................................................................................................................26
Figure 17. Acceptable operative temperature ranges. 90% acceptability limits = 90% of the occupants
experience a comfort condition; 80% acceptability limits = 80% of the occupants experience a comfort
condition. Source: ASHRAE 55-2010 (2010) ........................................................................................................27
Figure 18. Graphical description of the Required Sweat Rate model. Source: self-elaboration based on
Luna Mendaza (1994) .................................................................................................................................................29
Figure 19. Ventilation and air quality. Source: Allard (2002) ................................................................................31
Figure 20. Research methodology ............................................................................................................................32
Figure 21. Measurements devices: left, Tower 1 and Tower 2; right, Sensor 1 and Sensor 2 .........................33
Figure 22. Placement of the measurements devices in the sports hall ................................................................34
Figure 23. Air temperature measurements ..............................................................................................................38
Figure 24. Relative Humidity measurements ..........................................................................................................39
Figure 25. Air velocity measurements ......................................................................................................................39
Figure 26. CO2 concentration measurements .........................................................................................................39
Figure 27. The triple Sports Hall. Source: Consell Català de l’Esport (2005) ....................................................42
Figure 28. Climatograph of Barcelona. Source: self-elaboration based on AEMET (2011) ...........................43
Figure 29. Left: wind rose. Right: average wind velocity for each direction (m/s). Source: Servicio
Meteorológico de Cataluña ........................................................................................................................................44
Figure 30. Sports Hall 3D model ..............................................................................................................................45
Figure 31. TRNSYS building simulation. Building envelope characteristics .....................................................47
Figure 32. Use of artificial lights schedule. 1 = lights ON if the sports hall is occupied (natural light <300
lux); 0 = lights OFF (natural light>300 lux). Source: self-elaboration based on data provided by an
external collaborator ...................................................................................................................................................48
Figure 33. TRNFLOW natural ventilation simulation ..........................................................................................49
xii
Figure 34. Control strategy. Left: thermal comfort control; right: air quality control. Blue line: openings
behavior when the actual state of the natural ventilation system is ON. Green dashed line: openings
behavior when the actual state of the natural ventilation system is OFF ..........................................................52
Figure 35. TRNFLOW mechanical ventilation simulation ...................................................................................53
Figure 36. Demand controlled ventilation ..............................................................................................................54
Figure 37. Global cost calculation. Source: Ortiz et al. (2016a) ...........................................................................59
Figure 38. Comfort survey results ............................................................................................................................63
Figure 39. PMV index comparison. Tower 1 and Tower 2 indicate the results of the calculation
implemented following the Fanger model...............................................................................................................64
Figure 40. Thermal comfort classification according to the calculated PMV index .........................................65
Figure 41. Indoor operative temperature and comfort categories according to the UNE-EN 15251
standard .........................................................................................................................................................................67
Figure 42. Indoor operative temperature and comfort categories according to the ASHRAE 55-2010
standard .........................................................................................................................................................................68
Figure 43. Givoni diagram. Source: self-elaboration based on Al-Azri et al. (2012) ........................................69
Figure 44. Relative humidity comfort categories. Left: relative humidity registered along the two days of
measurements. Right: relative humidity and sports hall occupation ...................................................................70
Figure 45. CO2 concentration measurements and comfort categories ...............................................................70
Figure 46. System behavior during selected winter and summer control weeks ...............................................72
Figure 47. Air flow in the natural ventilated sports hall. FLNEL: net mass flow per link, TRNFLOW
output. FLNEL_NW: net mass flow through North-West opening; FLNEL_SE: net mass flow through
South-East opening .....................................................................................................................................................73
Figure 48. Discomfort hours. X-axis=discomfort hours; Y-axis=number of days ..........................................75
Figure 49. Energy consumption of occupied period in a summer weekday ......................................................77
Figure 50. Left: final energy; right: not renewable primary energy. The data elaborated in the figures
include heating, lighting and ventilation needs (other electricity consumption assumed equals to 12
kWh/m2, are not represented)...................................................................................................................................80
Figure 51. Cost-optimal analysis results. Orange line: lowest global costs level including heating system.
Green line: lowest global cost level without heating system ................................................................................82
Figure 52. Cost-energy evaluation: not renewable primary energy consumption vs. global cost over 20
years. Color map: green: natural ventilation without heating system; light blue: natural ventilation with
condensing boiler; blue: natural ventilation with heat pump; orange: mechanical ventilation with control;
pink: mechanical ventilation with variable speed fan; dark red: mechanical ventilation without control.
Light-blue circle: PV2 an PV6 configurations ........................................................................................................83
xiii
List of tables
Table 1. Sports Halls consumption ratios (Barcelona Provincial Council) .......................................................... 5
Table 2. Building concepts implemented in the Gerhard Grafe Sports Hall in Dresden-Weixdorf ............... 6
Table 3. Energy concepts implemented in the Gerhard Grafe Sports Hall in Dresden-Weixdorf .................. 6
Table 4. Construction features of the Sports Hall of the Cracow University of Agriculture. Source: based
on Kisilewicz 2015 ........................................................................................................................................................ 7
Table 5. Building concepts implemented in the Sports Hall of Nanyang Technological University in
Singapore. Source: self-elaboration based on The Singapore Engeneering (2015) ............................................ 9
Table 6. Energy concepts implemented in the Sports Hall of Nanyang Technological University in
Singapore. Source: self-elaboration based on The Singapore Engeneering (2015) ............................................ 9
Table 7. Energy efficiency strategies implemented in the German Grammar school Konigsbrunn. Source:
self elaboration based on IBOS-TGA......................................................................................................................12
Table 8. Energy efficiency strategies for Sports Hall proposed by the Step2Sport European project..........16
Table 9. Characteristic elements of natural ventilation. Source: self-elaboration based on Chenari et al.
(2016) .............................................................................................................................................................................20
Table 10. Wind tower operating principles .............................................................................................................20
Table 11. Thermal sensation scale. Source: self-elaboration based on Orosa Garcia (2010) ..........................24
Table 12. Coefficients for the calculation of Top depended on air velocity......................................................27
Table 13. Adaptive model parameters according to the ASHRAE-55 and EN UNE 15251 standards .......28
Table 14. Measurements configuration ....................................................................................................................34
Table 15. Occupation of the sports hall ..................................................................................................................34
Table 16. Metabolic rate .............................................................................................................................................35
Table 17. Clothing insulation .....................................................................................................................................35
Table 18. Survey answers. Clothing description .....................................................................................................35
Table 19. Exterior weather parameters ....................................................................................................................37
Table 20. Proposed n-ZEB strategies ......................................................................................................................40
Table 21. Sports hall occupation. (1° = Saturday; 2° = Sunday) .........................................................................43
Table 22. Sports Hall dimensions .............................................................................................................................45
Table 23. Thermal performance of the construction elements ............................................................................46
Table 24. Thermal performance of the windows ...................................................................................................46
Table 25. Building simulation: comfort parameters ...............................................................................................49
Table 26. Components of the simulated natural ventilation system ...................................................................50
Table 27. Control strategy. Opening factor variation ............................................................................................52
Table 28. Description of the mechanical ventilation system ................................................................................53
Table 29. Default values for the system loss categories ........................................................................................57
Table 30. Description of the evolutions rates implemented in the cost-optimal calculations. Source: Ortiz
et al. (2016a) .................................................................................................................................................................58
Table 31. Energy and environmental hypothesis for the cost-optimality analysis ............................................59
Table 32. Economic hypothesis for the cost-optimality analysis .........................................................................60
Table 33. PV system costs. Source: Huld et al. (2014) ..........................................................................................60
Table 34. System components costs .........................................................................................................................61
Table 35. Building category according to UNE-EN 15251..................................................................................65
Table 36. PMV index classification for Category IV .............................................................................................65
Table 37. UNE-EN ISO 7933 reference values for thermal stress and strain evaluation ...............................66
Table 38. Duration Limited Exposure .....................................................................................................................66
Table 39. Thermal comfort categories. Adaptive model UNE-EN 15251 ........................................................67
Table 40. Thermal comfort categories. Adaptive model ASHRAE 55-2010 ....................................................67
Table 41. Relative humidity categories according to the UNE-EN 15251 standard ........................................69
Table 42. CO2 concentration categories according to the UNE-EN 15251 standard .....................................70
Table 43. Natural ventilated building: discomfort results .....................................................................................74
xiv
Table 44. Natural ventilation. Deviation from the comfort limit values ............................................................75
Table 45. Mechanical ventilation. Discomfort results ...........................................................................................76
Table 46. Tested PV system configurations ............................................................................................................78
Table 47. n-ZEB energy balance. Terminology according to Sartori et al. (2012) ............................................79
Table 48. Covering factors of the different evaluated PV system configurations ............................................82
Table 49. Exterior façades composition ..................................................................................................................97
Table 50. Partition wall composition .......................................................................................................................97
Table 51. Roof composition ......................................................................................................................................97
Table 52. Ground floor composition .......................................................................................................................98
Table 53. Windows characteristics ............................................................................................................................98
Table 54. PV monthly shading losses (%). Skelion calculation ......................................................................... 101
1
1 Introduction
As reported in the article 2 of the European Union Directive 2010/31 (EPDB recast 2010) a “nearly zero
energy building” (n-ZEB), due to its very high efficiency, is characterized by very low energy
requirements, satisfied by significant extent through renewable sources available on-site or nearby. In
Spain energy requirements for new and refurbished buildings are set up, depending on building use and
climate zone, in the “energy savings” chapter of the Technical Building Code (Código Técnico de la
Edificación ‐ CTE, 2013). Each Member State (MS) is following a different path toward a more exhaustive
definition of n-ZEB, including for example specific building subcategories in their national energy plans.
More than half of the MS is managing sports facilities as a precise subcategory (D’Agostino 2015).
Energy performance improvements of sports facilities can significantly contribute to the fulfillment of the
article 9 of the EPDB, stating that MS shall ensure that all new public properties are n-ZEBs by
December 31, 2018 (EPDB recast 2010). Sports facilities have a relevant impact on the European energy
context. The European Union Sport and Recreational Building Stock is on average 30 years old and
characterized by a low efficiency level. It accounts for 1 million and half buildings, namely 8% on the
entire EU-48 Building sector. Specifically, 15’000 of the sports buildings are indoor sports halls. Those
numbers are bound to increase in the future, considering the yearly actual growth rate of 0.5 - 1.1% and
the constantly larger interest in sports and wellbeing (Sporte2 2013). However, new sports buildings risk
suffering the same processes that has already involved other building categories: became hermetically
closed and controlled at constant temperature in all climates (Santamouris and Wouters, 2006). Aiming to
reduce the energy consumption due to unnecessary infiltration and exfiltration, it has become increasingly
common improve the air tightness of the building envelope. As consequence, today mechanical ventilation
is considered a basic element buildings equipment. Moreover, the development of building management
systems (BMS) emphasizes and promotes the control of indoor environments within narrow limits. This is
very energy-intensive approach, with negative impact on energy utilization and, consequently, on the
environment (Kwon et al., 2013). In this regard, Aflaki et al. (2015) claim that the amount of energy
needed for cooling and heating buildings, due to the contribution of modern houses, has grown to 6.7%
of the total world energy consumption, with air conditioners consuming a major part of this.
Currently, up to 10% of the worldwide annual energy consumption is due to sports installations, which
represent 8% of the total consumption due to the building sector in some regions (Sporte2 2013). Some
countries have introduced performance-based requirements for new sports buildings: as examples, the
Norwegian overall net energy demand limit is 170 kWh/m2, while the Portuguese regulation sets to 233
kWh/m2 the maximum amount of consumed primary energy (Economidou 2013).
More than 200 net zero energy balance projects have been realized during the last 20 years (Musall et al.,
2010). However, most of them are located in North West countries and climates, where the availability of
economic resources, the degree of development of the technological sector, the knowledge of the specific
local energy and climate problems have facilitated the building renovation process. Spain occupies one of
the lowest position regarding the number of identified n-ZEBs, despite the suitable climate conditions.
Architects, engineers and policymakers all around the world have explored several solutions to realize n-
ZEBs. However, widen the range in which the buildings can ran freely, in practice without the activation
of mechanical systems, is an option still relatively unexplored, but that can produce important energy
savings (Santamouris and Wouters, 2006).
As stated by Allard (2002), to design an energy conscious building, it is fundamental to balance between
envelope performance, selection of appropriate heating, cooling and daylight systems and the attention
toward the preservation of acceptable indoor conditions, as ventilation effectiveness, air quality and
thermal comfort. Allard suggests that natural ventilation can play an important role in this context, and it
2
is especially suitable in recreational buildings in moderate or mild climate. In this regard, Florentzou
(2015) shows as the adoption of natural ventilation brings several benefits in large sports spaces, usually
mechanically ventilated. Through his studies, he verified that natural ventilation is a cheap, ecological,
simple and no space consuming solution that ensure optimal temperature in winter and preserves air
quality in summer.
1.1 Scope
The approach proposed in the thesis supports the design of a nearly zero energy sports hall in
Mediterranean climates, through the implementation of specific energy strategies. The goal is to guarantee
healthy environment to the final users of the building. For this reason, indoor thermal comfort condition
are evaluated in the different scenarios.
In line with the Trias Energetica principles (Brouwers and Entrop, 2005), the n-ZEB concept is achieved
implementing passive design and energy efficient measures in combination with renewable energy systems.
The work is focused on the study of an appropriate and effective natural ventilation system. The
advantages of the implementation of this technique are presented in relation to energy saving and cost-
effectiveness considerations. Moreover, taking into account that natural ventilation efficiency is strongly
dependent on high variable parameters, as wind characteristic and thermal state of the building, part of
this research is devoted to the identification of an adequate control strategy to ensure the optimal
functioning of the selected case-study sports facility.
1.2 Report structure
To improve the readability of this report, its structure is briefly explained. The present section aims to
introduce the work, including a brief description of the research context and of the problems correlated to
the Master thesis topic. The specific objectives and focal points of the thesis have been clarified.
The organization of the following parts of the thesis is presented:
Chapter 2: sets the basis of the developed research. The findings of a literature review
investigation are reported. It is presented an overview on real sports halls status, regarding their
distinctive energy needs as well as the already implemented n-ZEB strategies.
Chapter 3: illustrates the theoretical framework of the thesis. The attention is focused on the
description of the natural ventilation history, working principles and applications. The models
adopted in the research to perform the thermal comfort and air quality analysis are also
described.
Chapters 4 – 10: chapter 4 deals with the methodology applied for the development of the thesis.
The successive chapters explore in detail the different aspects and steps of the research. The
objectives, the execution and the collected data of the measurements campaign are described in
chapter 5. The selected n-ZEB strategies are presented and categorized in chapter 6. In chapter 7
the base case buildings characteristics are finally introduced, the studied sports hall is graphically
represented and the site-specific parameters are reported. Chapter 8 is fully devoted to the
explanation of the TRNSYS (SEL 2012) simulation. Ample space is assigned to the TRNFLOW
ventilation model, involving natural and mechanical ventilation. The natural ventilation modelling
phase is accurately illustrated (chapter 8.3), as well as the corresponding tested control strategy
(section 8.3.1). How the PV configuration analysis is performed through the software Skelion
(Skelion v5.1.9 2015) and the TRNSYS type 94 is described in chapter 9. The economic part of
3
the thesis is enclosed in chapter 10, where the cost-optimal methodology is defined and the
economical assumption made for the systems analysis are summarized.
Chapter 11: in chapter 11 is possible to find the outcomes of the different sections previously
described. The presented results are moreover discussed. Furthermore, an energy study of the
results is performed and elaborated in the energy balance available in section 11.3.1.
The report concludes with chapter 12, which includes the conclusion and suggestions for further
researches.
4
2 State of the art
The findings of a literature review investigation and an overview on real sports halls status are presented
in the following subchapters.
2.1 Sports Hall energy consumption
According to the findings of the European project Step2Sport, within which 26 pilot sports buildings
from seven EU countries have been subjected to energy audit, indoor swimming pools are the most
energy demanding sports installation. Spanish swimming pools on average consume 1’012 kWh/m2yr
(Radulov et al., 2014). The same research shows that sports halls are responsible annually for 13% of the
total energy consumed by sports facilities.
Sport halls are very large spaces with a specific energy demand profile, characterized by high level of heat
and electricity demand. Sports halls consumptions are closely related to the sport activity, the timetable of
the sports center, the public attendance during the matches and the site-specific climate conditions
(Artuso and Santangeli 2008). For instance, sports halls in the continental European zone require double
amount of energy (about 490 kWh/m2) than the Mediterranean ones (Trianti-Stourna et al., 1998).
Aelenei et al. (2015) analyzed the primary energy consumption share per building category at country level,
in Europe. As it possible to see in figure 1, their results show that sports facilities are responsible for a
significant part of Spanish total primary energy consumption.
More in detail, the Catalan region of Spain alone accounts for 2’417 public buildings identified as sports
facilities, covering 1’338’104 m2 of total built-up floor area (6’061’595 m2) and responsible for 14% of the
total primary energy consumption of the public building stock. Specifically, sports pavilions use 238
kWh/m2 every year (Radulov et al., 2014) and only around 1.3% of the sports facilities have the energy
performance certification, that according to the Spanish regulation is based on computer simulation (six
official software tools allow to compare the building with a reference building, considered as an average
building over more than 100.000 computer simulation) (Gunnarsson et al., 2015).
The results of the investigation conducted by ICAEN (2012) suggest that more than half of the current
Catalan sports halls energy consumptions are related to lighting (56%), a relevant energy use is due to
domestic hot water (28%.), while heating and ventilation demand accounts for 4% of the total (other
consumptions are estimated about 12%). Predicting that through the implementation of energy efficiency
Figure 1. Analysis of primary energy consumption share per building category at country level. Source: Aelenei et al. (2015)
5
improvements a significant reduction in primary energy use can be achieved, an energy efficient scenario is
also proposed. In this case, the primary energy consumption reaches the value of 128 kWh/m2. The
available data are elaborated in figure 2. From figure 2 it results evident that significant energy savings are
expected from lighting, DHW and heating (including ventilation) demand reduction.
Finally, it is reaffirmed that sports hall energy consumptions are strongly linked to the number of users of
the installation. In this regards, it is possible to examine the data made available by the Barcelona
Provincial Council (Diputació de Barcelona 2016) referred to the Catalan sports facilities and summarized
in table 1.
Table 1. Sports Halls consumption ratios (Barcelona Provincial Council)
Surface (m2) Liter of water/user Electricity (kWh/user) Fuel (natural gas) (kWh/user) Euro/user
1’600-2’300 20-40 0.15-0.5 1-2 0.2-0.6
2’100-3’000 20-40 1-2 1-2
2.2 Nearly Zero Energy Sports Halls
The previous section dealt with the estimation of the specific energy consumptions of Catalan sports halls.
Generally, few researches have been conducted regarding the energy behaviour of sports buildings. An
example is the energy audit performed by Trianti-Stourna et al. (1998) for a representative number of
Hellenic indoor sports facilities built between 1970 and 1980. The authors proposed passive solar
retrofitting interventions. The result of the study shows that, for small and medium-sized sports centers,
annually from 55% to 95% of heating consumption can be covered implementing architectural solutions
as insulation of the external walls, creation of South-facing clerestories, and supplementary sun spaces,
installation of shading devices and appropriate ventilation systems. Additionally, according to their
research, a reduction of the electricity demand, along with the improvement of the indoor thermal
comfort conditions, can be achieved taking advantage of natural light and ventilation, and installing heat
recovery systems in traditional heating and ventilation mechanisms.
Following, real cases study regarding the implementation of energy saving measures in existing sports
facilities are presented.
ICAEN ICAEN efficient0
50
100
150
200
250
En
erg
y (
kW
h/m
2)
Electricity Natural Gas
Other DHW_solar
DHW_fuel Lighting
Heating
Figure 2. Catalan Sports Hall primary energy consumption (kWh/m2). Heating includes ventilation. Source: self-elaboration based on data ICAEN (2012)
Total
primary
energy
6
The research project developed by the Institute of Power Engineering at TU Dresden, the Fraunhofer
Institute for Solar Energy Systems and “Am Königswald” Planungsgesellschaft mbH, is focused on the
building operation analysis and on the optimization of the Gerhard Grafe Sports Hall (EnOB 2009)
situated in Dresden and built in 2006 (Felsmann et al., 2015). In this case study, the energy efficiency and
thermal comfort targets are achieved implementing building and energy concepts. The adopted building
concepts are summarized in table 2 while the main characteristics of the energy system optimization
strategies are reported in the table 3.
Table 2. Building concepts implemented in the Gerhard Grafe Sports Hall in Dresden-Weixdorf
Building concept features function
Opaque
components
Concrete perimeter
wall
thermal activated component
high thermal mass
high inertia
constant indoor temperature
passive cooling
Monolithic structure compactness reduction of transmission
heat losses
Rainscreen cladding weather protection
Transparent
components
Windows surface South-East elevation 20% less
than North and West
Windows vertically angled ribbon homogenous lighting glare free
Glass low solar energy
transmittance factor glare reduction
Table 3. Energy concepts implemented in the Gerhard Grafe Sports Hall in Dresden-Weixdorf
Energy concept features function
Energy
savings
measures
Ventilation system
moisture-led ventilation in the sanitary and changing rooms
CO2-led ventilation in the hall
reduction of ventilation need
high energy efficiency heat recovery
ground-air heat exchanger
reduction of the heat supplied at the external air
Heat
Absorption natural
gas heat pump heat generation
Boreholes in the
ground
heat source for the heat pump
heat sink for cooling
Collector and
distribution centre
steel distributors/collectors
5 thermally separated temperature chambers
specific temperature for different heat zones
no mixed temperatures
Solar thermal
system provides 70% of the heat along
all the year DHW
Condensing boiler modulated peak load backup system
Buffer storage tanks 1’200 litres
storing surplus solar thermal
balance
7
Overall, the system achieved 35% reduction of gas consumption, good indoor thermal comfort and
reduction in heating and primary energy requirements.
The sports hall of the Cracow University of Agriculture is an additional example of sports facility designed
according to the German passive house standard (tab.4) (Kisilewicz and Dudzińska, 2015).
Table 4. Construction features of the Sports Hall of the Cracow University of Agriculture. Source: based on Kisilewicz 2015
Thermal transmittance of the external walls 0.1 W/m2K
Triple glazed windows 0.8 W/m2K
Total solar transmittance g = 0.6
Mechanical exhaust-supply ventilation + air heater +
recuperator Heat recovery efficiency = 75%
Electrical external blinds Shading South and North orientated
windows
West and East façades Glazed
Building orientation Large East and West windows
Insulated green roof
Radiant water floor heating system
Final energy for heating <15 kWh/m2 ; air tightness, n501= 0.2 h-1
However, the focus of the research conducted by Kisilewicz and Dudzińska (2015) is the investigation of
the summer overheating phenomenon occurring in the passive building. The authors measured the
internal microclimate parameters during two summer days, when there was no occupancy, the mechanical
ventilation system was not operating and the windows were closed. The collected results suggest that 33%
(90% in extreme conditions) of the sports hall users would be dissatisfied with the recorded thermal
conditions, due to the excessive increase of indoor temperature. The study indicates that the costs of a
mechanical cooling system can be avoided implementing accessible measures against overheating, as
windows blinds. Moreover, considering the favourable condition of significant lower outside air
temperature respect to the internal one, the researchers propose an intensive adoption of night cooling,
aimed at discharging the internal thermal capacity of the building.
Tsoka (2015) simulated (through Pleiades-Comfie software developed by the Center of Energy and
Processes of Mines-ParisTech) and analysed different design strategies for the Michel Walter stadium in
Strasbourg. The objective is to achieve the highest possible energy efficiency and simultaneously to avoid
thermal discomfort in summer periods. The studied building is designed to reduce the annual heating
energy demand: the interior concrete wall provides additional thermal mass, the heat transfer coefficients
of the buildings components are between 0.13 and 0.18 W/m2K, the windows are doubled glazed with
aluminum thermal brake frame and a U-value of 1.40 W/m2K, the large openings harvest solar gains.
However, the high inertia of the building increases the risk of summer overheating. The research shows
that vertical solar shading devices can decrease electricity consumption for air conditioning and improve
indoor conditions, achieving a reduction of the ratio of the occupied time during which the internal zone
temperature exceeds 27°C to the total occupied period, between 42.83% and 55%. In addition, a solution
including shading deciduous trees 6.5 meters high and the activation of natural ventilation in the offices
adjacent to the sports halls (only during occupied time and in case of indoor air temperature 2°C above
outdoor air temperature), has been evaluated. It has been proved that this configuration reduces the
number of occupied hours during which the indoor air temperature exceeds the maximum acceptable
comfortable temperature of 27°C, between 30.6% and 35.1% compared to the previous case. The most
1 n50 is the parameter that indicates how often the air volume of the building is exchanged per hour at a pressure
difference of 50 Pa (AENOR 2002a)
8
effective measure to reduce summer overheating results the implementation of nocturnal mechanical
ventilation (from 23:00 pm to 9:00 am, when interior temperature is 2°C higher than exterior
temperature). According to this simulation scenario, during summertime air temperature does not
exceedes the limit of 27°C for more than 50 hours.
The study conducted by Flourentzou et al. (2015) investigates the performance of another construction
designed as a typical passive building, including 10 classrooms and a gym, in Switzerland (Commune de
Savièse) (fig.3). The high volume of the gym has been analysed in detail. The aim of the research is to
provide a stack effect of 6000 m3/h without extra costs. The performance of a natural ventilation system
are assessed. The designed natural ventilation configuration requires two opening of 4 m2 on the top and
on the bottom of the space (the same used to comply with the fire regulation) and 2 additional lateral 1 m2
openings for better air distribution. Overall, natural ventilation results to be more efficient than
mechanical ventilation with heat recovery: the height of the building creates a high stack effect while the
large volume creates a large reservoir of fresh air, making possible the exploitation of infiltration for
ventilation. The energy consumption for fans is completely avoided. In this particular case study, air path
and light path are dissociated. Moreover, during summer ventilation is controlled by the difference
between indoor and outdoor temperatures (fig.4); during winter natural ventilation activation is related to
the indoor air quality, expressed in CO2 concentration (fig.5).
Figure 4. Sports Hall in Commune de Savièse in Switzerland. Source: Flourentzou et al. (2015)
Figure 3. Summer ventilation. Night ventilation: the fresh air enters on the basement and goes out from the top openings. Source: Flourentzou et al. (2015)
Figure 5. Winter ventilation. Air enters from the top lateral openings and goes out from the top front opening in order to avoid cold draughts. Source: Flourentzou et al. (2015)
9
The Nanyang Technological University in Singapore (The Singapore Engeneering 2015) designed a new
sports hall with the intention to achieve 35% reduction in water and energy consumption and waste
production by 2020. The adopted sustainable measures are summarized in the tables below (tab.5 and
tab.6) and graphically represented in figure 6 and figure.7.
Table 5. Building concepts implemented in the Sports Hall of Nanyang Technological University in Singapore. Source: self-elaboration based on The Singapore Engeneering (2015)
Building concept features function
Opaque components
Engineered wood
system:
glued laminated timber with panels linearly aligned
cross-laminated timber
heat insulation
Table 6. Energy concepts implemented in the Sports Hall of Nanyang Technological University in Singapore. Source: self-elaboration based on The Singapore Engeneering (2015)
Energy
concept features function
Energy savings
measures
Natural
ventilation
designed analysing wind and sun patterns on site
operable louvers
reduction of the need of mechanical ventilation
Cooling
Passive
induction
air
conditioning
provides cold air at the floor level
chilled water coil cool the warm air at the high level (fig.7)
temperature stratification: only the occupied zone is cooled
avoid the need of a fan: convective force provided by the heat source in the space
avoid the need of metal ducting avoid condensation and draughts
Chiller auto condenser-tube
cleaning system
prevent fouling and scaling maintain good heat transfer
Lighting
Maximising natural light
daylight sensors
East and West walls with top light shelf
double skin wall in the West
reduction of artificial light requirements
diffusion of the light in the Sports Hall
reduce sun radiation intensity
Artificial lighting
LED lamps
zoning
motion sensor
reduction of the operating wattage
variable lighting to suit the needs
Water
Water sub-meters for the cooling tower
monitoring water usage
Heat recovery system
provide hot water for shower
avoid use of conventional electric heater
10
Rajagopalan and Luther (2013) analysed the indoor enviromental conditions (thermal comfort, CO2
concentration and temperature stratification) of a sports hall in an aquatic center in Australia (temperate
climate), to then identify potential strategies for low energy conditioning. Also exterior weather data have
been collected during their research. The studied sports hall was not equipped with a cooling system; there
were three exahust fans in the ceiling to assist the ventilation. Evaluating the current building conditions,
the researchers verified that the users of the sports hall experiece periods of great discomfort due to high
indoor temperature. Conversely, the CO2 and the relative humidity levels resulted good. The authors
Figure 7. Chilled water coils, at a high level, used to cool down warm air. Source: The Singapore Engeneering (2015)
Figure 6. Energy efficiency strategies implemented in the Sports Hall of Nanyang Technological University in Singapore. Source: The Singapore Engeneering (2015)
11
proposed a set of strategies to improve thermal comfort and reduce energy consumption of the sport
facility:
direct evaporative cooling: to take advantage of periods when exterior temperature is high and its
moisture content is low;
shading: to reduce discomfort in hot days, blocking part of the solar radiation to reach the glass;
control and monitoring: to shut down the ventilation during several hours, depending on the indoor
air quality conditions;
night purging: to cool down the indoor space, preparing the room for the hot day ahead;
optimization of the exhaust fans and openings position: through a CFD simulation, it has been
verified that more air movement occurs when the exhaust fans are at lower level. Moreover, it resulted
that the air movement profile could be further improved replacing the exhausts fans with opening, as
in natural ventilation mode.
The passive sports hall of Slomniki, Poland, is presented as a successful example within the CEC5 project-
Demonstration of energy efficiency and utilisation of renewable energy sources through public buildings (fig.8) (CEC5
2014). The sports hall is the first Polish passive public building with a quality certificate awarded by the
Passive House Institute. The solutions implemented in the building achieved 87% energy use reduction
and 90% CO2 emissions reduction. Wood-derived materials have been used as construction elements. A
mechanical ventilation system with heat recovery has been installed. The orientation of the building and
the position of the windows have been designed to acquire most of the sunlight during winter.
Conversely, the position of the windows has been also assessed to minimize the sunlight during summer
and a roller shutter system has been adopted to prevent overheating.
Within the framework of the European Union Green Building project (European Commission, Joint
research centre – Energy Efficiency, 2016a), a voluntary programme started in 2005 that aims to improve
energy efficiency of non-residential buildings in Europe, the German Grammar school Königsbrunn -
school sports centre (European Commission, Joint research centre – Energy Efficiency, 2016b) is a
successful example of building refurbishment. The energy efficiency strategies implemented in the sports
center achieved 44.81% energy savings. Specifically, consumptions decreases from 648.93 kWh/m²yr,
registered before the renovation, to 358.14 kWh/m²yr.
Table 7 reports a summary of the thecniques adopted to contain energy consumptions and,
consequentely, the high operating costs of the sports facility (IBOS-TGA).
Figure 8. Summer ventilation in the Passive Sports Hall of Slomniki. Source: CEC5 (2014)
12
Table 7. Energy efficiency strategies implemented in the German Grammar school Konigsbrunn. Source: self elaboration based on IBOS-TGA
Building
envelope
Heat
insulation:
mineral rock
wool rear
ventilated
Walls Exterior 25 cm
Facing the inner courtyard 12 cm
Basements
Walls or ceilings to rooms 12 cm
Walls or floor
slabs in
contact with
the ground
On the outside walls 12 cm
On top of the floor 14 cm
Roof 40 cm
Transparent
components
Glazing Coated double
glazing
Window frame Wood
Miscellaneous
Ratio area/volume and
compactness Atria covered with a glass roof
Exterior mobile shading on the
roof
Automatic positioning according to the
sun altitude
Vertical façade under the roof ridge that can be open completely to remove
warm air
Floor ducts to direct cool air into the courtyards
HVAC-
system
Supply
systems
Heating and sanitary water
production
District heating
(184 kW)
Electricity PV on the roof
(1’140.9 m2; 155’478 kWh/yr)
Ventilation
concept
Supply air Well water
Cooling: 10-15 °C
Heating: 9-4 °C
Filtering
Heat recovery
Rotary heat exchanger (81%)
Freewheel regulated by frequency
converter
Pressure control to regulate the flow rate
Radiators
Lighting T5 lamps Control
Light sensor
Local and central switches
Presence detectors
13
In the town of Unterschleißheim (Germany), it has been realized a passive sports hall to serve the needs
of the adjacent school and to be used by private sports clubs and by the local community for local events.
The technical features of the building are reported in the figure 9 (SEAI 2010). It is important to highlight
other interesting design aspects of the sports facility, which contribute to the achieved energy use
minimization, high comfort levels and optimal indoor air quality. To balance between providing sufficient
light for the users of the sports hall, whilst also minimising use of artificial lighting, the transparent
components have been carefully dimensioned and roof windows equipped with louvers, installed to
provide additional day lighting and to prevent overheating. The choice of the ventilation system capacity
has been a crucial aspect of the project. Avoiding to size the system for the larger, but less frequent,
occupational patterns, large operable windows have been installed. Basically, an hybrid system of
mechanical and natural ventilation has been implemented.
Also the refurbishment of the sports hall located in Lorch (Germany) (fig.10), operating since 1976, has
been realized according to energy efficiency principles (BEHNISCH ARCHITEKTEN 2015). Similarly to
the previous cases, the technical solutions implemented to avoid summer overheating and glare problems
include the installation of plastic skylights and of movable external solar shading on all the transparent
façades, except for the Northern one. The ventilation functions have been separated from the heating
ones. The ventilation system is based on the displacement principle, to avoid draft and noise extraction of
pollutants. It operates in combination with the natural ventilation contribution of openable windows.
Figure 9. Building features of the Sports Hall in Unterschleißheim. Source: SEAI (2010)
14
Additionally it is equipped with high efficient heat recovery system. The external fresh air is pre-heated in
winter, and pre-cooled in summer, passing through an underground duct; than, it goes to the equipment
storage room, the hall, the changing room and finally it is extracted through the toilets and shower rooms.
The users have the possibility to control the system and adjust it according to their needs. Finally, process
water is heated by a solar heating system and thermal energy is supplied through the local biomass heating
network.
The designer of the sports centre in Wageningen, Netherdlands (Reijenga 2005), aimed to realize a
bioclimatic sports building implementing sustainable and low energy strategies. The project regards two
sports halls (used by high-school students during the week and for competitions at weekends), an office
tower, a canteen, an indoor climbing wall and a fitness area, all situated around a central unheated outdoor
area called “the Plaza”. The areas of the building are used for both energy concepts and sports
functionalities, according to integral design techniques. The most innovative aspect of the construction is
the optimization of the energy-saving natural ventilation system, which includes different components:
Solar chimney: it consists of a high wall of offices with a glass cavity in front that is smaller nearer
the top. At the top of the ventilation tower there are a wind vent cowl, that ensures that the
opening is always on lee-side, and a ventilator, characterized by a low resistance when is not
turning, to allow the ventilation air to pass naturally. Moreover, at the top of the solar chimney a
heat pump recovers the heat from the ventilation air and returns it via the heating and domestic
hot water system, as in balanced ventilation systems (fig.11, fig.12);
Glass-covered area (the Plaza);
Self-regulating grills in the sport halls.
Figure 10. Sports Hall in Loch. Source: BEHNISCH ARCHITEKTEN (2015)
15
The energy generation installations, in addition to the heat pump, include high-efficiency boiler (cascade
format), a solar boiler with 60 m2 of collectors on the Plaza roof and a PV system. The PV system covers
2448 m2, includes transparent and solid panels and has a total output power of 281.8 kWp. The solar
panels in the roof can reduce the amount of direct sunlight entering the building of 30%, contributing to
avoid the risk of overheating. Overall, it results that for the entire structure the calculated energy
consumption is about 60% lower than usual and the energy performance coefficient (EPC) is about 0.37.
As mentioned in section 2.1, lighting system in sports facilities is responsible for a large amount of
electricity consumption. In this regard, a further case study is presented. In the Universida Autonoma
Metropolitana (UAM) in Mexico City (Castorena et al., 2011) the current needs of light appliances,
composed of 50 Lithonian 400 Watts high pressure sodium lamps (ModelTH-A16), correspond to 240
kWh per day, 1680 kWh per week and 7200 kWh per month. Aiming to reduce this significant electricity
consumption and the related high economic load, the researcher evaluated the possibility to install
sunducts in the facility. Sunducts are lighting systems that, through a collection system with mirrors,
enable natural light to reach zones which would be dark under normal conditions. The results of the study
show that the installation of these devices can achieve important improvements in the illuminance levels
of the sports hall. Considering the regular schedule of the activity (from 10 am to 10 pm), for 50% of the
use time, 380 lux can be provided indoor in condition of overcast sky and 1600 lux in condition of clear
sky. Currently, the registered daylight illuminace level with artificial light system off is on average around
50 lux. The installation of sunducts results to be an energy saving alternative that contribute to the
traditional lighting system of the sports hall taking advantage of the natural light.
Finally, according to the reports published as part of the Step2Sport European project (Torrentellé and
Escamilla, 2015) (LEITAT & SEA 2015) and aimed to support the refurbishment of existing sports
buildings through step by step renovation towards n-ZEB standards, sports facilities across European
countries have common energy efficiency problems. The proposed improvements are summarized in table
8. It is expected that the implementation of these measures achieves on average 60% reduction of energy
use per gross floor area in typical sports halls.
Figure 11. Left: the wind cap. Right: interior view of the solar chimney. Source: Reijenga (2005)
Figure 12. Ventilation tower: summer ventilation (left); winter ventilation (right). Source: Reijenga (2005)
16
Table 8. Energy efficiency strategies for Sports Hall proposed by the Step2Sport European project
Enegy efficiency
measures Function Saving potential
Building
components
External wall insulation Prevents heat gains and losses 10%-15% of heating and
cooling demand
Cavity wall insulation Reduction of heat losses 10%-25% of heating
demand
Thermal roof insulation Prevents heat gains and losses 33% of heating and cooling
demand
Double and triple
glazing windows
Prevent bi-directional heat
transfer
2%-22% of heating and
cooling demand
Shading solution Prevents heat gain and glare 10%-25% of cooling load
Storage
solutions
Stratified buffer thank
for hot water Increase heat storage efficiency 20-35%
Lighting
LED lighting Provides cost cut and improved
light quality
15-60% of lighting energy
consumption
Lighting control system Provides the righ amount of ligh
when and where it is necessary
20-50% lighting energy
consumption
Natural daylight system
- Sunpipe
Directing sunlight into a room
from roof level 75% during day time
Ventilation
Ventilation units with
heat exchanger
Up to 85% efficiency in recovery
heat from exahaust air
50%-85% of thermal
energy for heating of
supply air
Optimization system for
ventilation units
Reduce the number of operational hours
Reduce airflow
10%-80%
Control
strategies
Building energy
management system
To suit the use and the
occupancy level of the Sports
Hall
Up to 25%
Digital time switches Turn off the equipments when
they are not used
1%-7% of the total energy
consumption
Energy
production
Photovoltaic system Electricity production 40-65%
Solar thermal system Hot water production 60%
Geothermal heat pump Heating and cooling
Production of hot water 25%-65%
Biomass boiler Heating 2%-5%
Cogeneration –
Combined heat and
power
Provides heat and electricity 20%-35%
Efficient condensing
boiler
Recovery of the latent heat –
incresed efficiency 5%-20%
17
3 Theoretical framework
The following subchapters illustrate the theoretical framework of the thesis research. The theoretical
aspects regard the natural ventilation working principles as well as the description of the adopted comfort
models.
3.1 Natural ventilation
The term ventilation refers to the practice of replace stale indoor air with fresh external air (Chenari et al,
2016). Why is it necessary to ventilate a building? Ventilation functions are briefly listed below.
Supply oxygen for respiration
Dilution of indoor contaminants
Control of indoor aerosol concentration
Control of indoor relative humidity
Optimization of air distribution.
Natural ventilation achieves the mentioned objectives without the support of a mechanical system.
Natural ventilation has been used since ancient time to ensure acceptable condition in inhabited spaces.
Several technical solutions have been implemented along the human history to take advantage of the
natural ventilation phenomenon. Allard (2002) mentions the Native America tipi, the Mongolian yurt and
the Iraqui ma’dam as examples of traditional buildings located in hot and temperate climate that adopted
wind-driven ventilation techniques. Further examples of wind-stack driven ventilation devices are
provided by the Iranian traditional architecture that used curved-roof air vent, wind tower (dating back to
300 BC), cistern and ice maker systems (appeared about 900 AD). It is proved that wind catches, or
malkaf, appeared in the ancient Egyptians houses since 1300 BC. While ventilated atria and courtyards,
attached to vernacular buildings to promote natural ventilation effects, were used in Greek and Roman
architecture, in Mesopotamia, in Cina, in the Indus and in the Nile valley (Santamouris and Wouters,
2006). Furthermore, a ground-cooling ventilation system, called covoli, was mentioned in an Italian
architecture book for the first time in 1570 (Allard 2002).
In this section functioning principles and preeminent characteristics of natural ventilation are presented.
3.1.1 Natural ventilation driving forces
Generally, a natural ventilated building is one for which ventilation occurs trough openings in the
envelope (Etheridge 2015), as effect of pressure difference established across them. Santamouris and
Wouters (2006) describe the physical principles which natural ventilation in based on. Specifically, airflow
is generated through wind velocity and thermal buoyancy effects.
The time mean pressure induced when wind flow comes into contact with an object can be expressed as:
𝑝𝑤 = 𝐶𝑝 𝑤∗ 𝜌𝑤 ∗ 𝑣𝑤
2 /2 (eq. 1)
where 𝐶𝑝 is the static pressure coefficient and 𝑣 is the time mean wind speed at given level, usually at the
high of the building or openings. Referring to the convention according to which the pressure difference
between the interior of the building and the exterior environment is positive when the building is
pressurized respect to outdoors, the wind force make that the air is driven into the building entering from
the openings in the windward side. Conversely, the air is driven out passing through the openings located
in leeward side of the envelope.
18
Wind and buoyancy work in combination to determine airflow. To define the buoyancy effect it is
necessary to introduce the static pressure, presented here in its derivate form:
𝑑𝑝𝑠 = −𝜌𝑎(𝑧) ∗ 𝑔 ∗ 𝑑𝑧 (eq. 2)
Looking at equation 2, it must be taken into account that air density depends on temperature and that the
order of magnitude of pressure differences in ventilation systems is significantly lower than the
atmospheric pressure (𝑝𝑜= 1.325 Pa). Therefore, considering the gas law in isobaric transformation and
the temperature constant on vertical direction, the following equation can be applied:
𝑝𝑠 = 𝑝𝑟𝑒𝑓 − 𝜌0 ∗ 𝑔 ∗𝑇0
𝑇𝑧𝑜
∗ 𝐻 (eq. 3)
where subscript 0 indicates the standard conditions for the dry air, 𝑝𝑟𝑒𝑓 is the reference pressure at the
height z0 and ℎ the established high difference. Essentially, equation 3 describes the natural phenomenon
according to which warmer air, with lower density, is forced to move upward by colder air, with higher
density.
Moreover, it is introduced the expression that allows to evaluate the airflow through an opening. Equation
4 derives from the Navier-Stock equation:
∆𝑃 = 0.5 ∗ 𝜌𝑎 ∗ 𝑄2/(𝐶𝑑 ∗ 𝐴)2 (eq. 4)
Cd is a dimensionless parameter depending on opening geometry and Reynolds number; A is the opening
area and 𝑄 is the mean air flow rate expressed in m3/s.. However, the reported expression is applicable to
small orifices through which air infiltrates and it is obtained for fully developed flow. This last condition
generally is not verified in real building, where the openings have not a uniform geometry. Therefore, in
real case studies, when the behavior of small and large openings must be analyzed, it is necessary to apply
empirical lows. Generally, the power law expressions have the form (Allard 2002):
𝑄 = 𝐾 ∗ (∆𝑃)𝑛 (eq. 5)
where 𝐾 is the flow coefficient that varies according to the building geometry; 𝑛 is the flow exponent,
determined from experiments and without a physical meaning, it specifies if the flow is turbulent or
laminar.
The equations from 1 to 5 are extrapolated from Santamouris and Wouters (2006).
3.1.2 Natural ventilation strategies
To take advantage of natural ventilation principles, different ventilation strategies can be implemented,
determining the patterns according to which the air enters and exits from the building (Santamouris and
Wouters 2006).
Single side ventilation
It is the most localized technique, realized installing opening only in one side of the ventilated space. The
air enters and exits alternatively from the upper and lower part of the opening. The fluctuation component
of the wind is the main drive force of the air movement. The range of effectiveness of this solution is
19
limited to a maximum room depth of 2.5 times the ceiling height that has to be about 2.5m. Moreover, to
maximize the single side ventilation effect, window should measures 1/20 of the floor area.
Cross-ventilation
Cross-ventilation is achieved through the installation of openings in opposite side of the building
envelope. It occurs when air enters into the building from one side, traverse the entire indoor space, and
leaves from another side. Therefore, this technique is able to provide ventilation for a whole building
floor.
Stack ventilation
The air movement generated by thermal buoyancy is known also as stack effect and it is typical of tall
buildings where the pressure difference generated by the density difference, mainly during summer, forces
interior warm air to rise. An over-pressure is created at the top of the building and consequently air flows
out. The outdoor cooler air, entering from lower inlets, will replace it. The level at which the indoor and
the outdoor pressures are equal is called neutral pressure level (NPL), and it correspond to the absence of
air movements.
The three main ventilation strategies can be also implemented simultaneously, as shown in figure 13
(Axley 2001). Other measures can be considered in the building design to improve natural ventilation
effectiveness. In figure 13 an inslab is represented. Its function is to increase the control on air distribution
and temperature.
Figure 13. Schematic of mixed local/global and stack/wind ventilation strategy. Source: Axley (2001)
20
3.1.3 Natural ventilation technical solutions
According to the classification proposed by Chenari et al. (2016), the technical solutions so far available to
take advantage of the natural ventilation principles, can be summarized as in table 9:
Table 9. Characteristic elements of natural ventilation. Source: self-elaboration based on Chenari et al. (2016)
Element/features Natural ventilation principles Supply or Exhausted
Atrium Single-sided, Cross and Stack Supply and Exhaust
Wind scoop Cross and Stack Supply
Wind tower Cross and Stack Exhaust
Wind catcher Cross and Stack Supply and Exhaust
Ventilation shaft Single-sided, Cross and Stack Supply and Exhaust
Solar Chimney Cross and Stack Exhaust
Ventilation openings on façade Single-sided, Cross and Stack Supply and Exhaust
Double-skin façade Single-sided, Cross and Stack Supply and Exhaust
Aflaki et al. (2015) present other architectural elements able to promote natural ventilation effects, as
balconies, wall grooves and corridors, which helps to create cross ventilation by channeling and delivering
air flow from outdoor into different parts of a building.
Some of the mentioned technical solutions are described more in details.
Wind towers provide natural ventilation maximizing the pressure difference between inlet (positive
pressure on the wind ward side that drives the fresh air into the room) and outlet (negative pressure on
the leeward side to extracts the stale and warm air) of the building. A wind tower takes advantage of
different physical principles according to the interior and exterior climatic conditions, as summarized in
table 10 (Allard 2002):
Table 10. Wind tower operating principles
Mechanisms Effect
No wind during the day Downdraught The air, cooled through the tower wall, sinks down
Wind Wind effect The air flow faster and is cooled more effectively
No wind at night Updraught
(stack effect)
The air, warmed up through the tower walls with
enough thermal inertia (the tower releases at night
the heat absorbed during the day), moves up
Traditional wind towers can be classified in four main categories (Dehghani-sanij et al., 2015):
one-sided wind tower: there is only one opening in the dominant direction of the wind;
two-sided wind tower: it is designed to blow and suck the airflow into the building;
four, six, eight-sided wind towers: the dimensions are related to the local climate conditions;
cylindrical wind towers.
The construction elements that characterize wind towers have evolved along the history of architecture to
adapt to different climate needs and aiming to improve efficiency. The main limitations related to wind
tower implementations have been the difficulty of rotating in the direction of maximum ambient air, the
poor interior recirculation and the need for an outward wind characterized by sufficient speed.
Researchers investigated the integration of wind towers in modern buildings. The wind tower design
proposed by Bahadori et al. (2008) takes advantage of the evaporative cooling potential of the air. It
includes wetted columns, realized through unglazed ceramic conduits uniformly sprayed of water, or
wetted surfaces, consisting of straws or cellulose called pads, usually used in evaporative coolers, and
21
placed at the top of the device. Dehghani-sanij et al. (2015) designed a wind tower model to be adopted in
residential buildings, closed arenas, and commercial and administrative buildings as passive ventilation
strategies. The main features of the proposed wind tower is the possibility of rotating in the direction of
maximum wind speed, detected through a wind vane. The considered wind tower is meant to be used in
combination with one or more windows, a solar chimney or another wind tower installed in the opposite
direction.
The use of the wind tower devices in cold climate is related to the integration of heat recovery systems. In
this regarding, Calautit et al. (2016) studied the performance of a natural ventilation system realized with
heat pipes and heat sinks integrated in a multidirectional wind tower channel. The researchers achieved an
increment of the supply air temperature by up to 4.5 K.
Traditional wind towers can be installed in connection with an additional channel positioned at 5-7 meters
underground and called naghb in Persian (Jafarian et al. 2010). It uses the ground humidity to cool the air,
operating as a ground-air heat exchanger. The system is effective also when there is no wind, because the
ambient air that enters the naghb, passing through the openings on the wind tower sides, is cooled through
an evaporative processes. Consequently, the cool heavier air replace the interior warm air resulting in a
natural ventilation air movement. When the wind is blowing, the air passes through the underground
channel, enters in the building and goes outside from windows and doors. By analogy, the benefits related
to the high inertia of the soil, namely the ability to keep the surrounding air temperature almost constant
along the year, are the key functioning aspects of the covoli, the ground cooling ventilation system
implemented in a group of sixteenth century villas in Italy (Allard 2002). The system is based on
interconnected sloped caverns, located underground and used as cool reservoirs. The covoli are linked to
the outside, to create a downdraught of cooler air during the summer and an updraught during the winter,
and to the villas, placed at lower level. The Canadian or Provencal well are modern examples of ground-
cooling ventilation principles application (Touzani and Jellal, 2015). This kind of installations are passive
thermal solutions that use soil as seasonal dumper. Specifically, the Canadian well is intended to warm the
fresh air in the winter and the Provencal well to cool it in summer.
A similar design has been studied in a university campus in Malaysia. Sanusi et al. (2013) present an
underground cooling system as a passive cooling alternative to the air-conditioning. The investigated
technology includes polyethylene underground-buried pipes. Ambient air is conveyed to the pipes to use
the soil as heat sink. The results of the investigation show that the air passing through the pipes
experiences a relevant temperature drop, up to 6.4 °C and 6.9 °C depending on the season of the year.
Alba et al. (2013) provide an additional example performance study of a ground cooling combined with
natural ventilation system. Their research regards an industrial building located in the city of Cali,
Colombia, a typical hot humid location. In the studied building, the natural ventilation strategy is
implemented through the installation of louvers at the bottom of the façade and a ventilated skylight at
the roof, while the interior temperature is controlled through shading devices and a good thermal
insulation. The simulation of the integration of an earth-air heat exchanger in the described system shows
that, without extra energy consumption, an ambient internal temperature of 28.5°C can be achieved,
namely 3°C lower than the case with natural ventilation alone.
There are several possibilities to promote natural ventilation in modern buildings through the
implementation of passive solar strategies. Considering architectural roof and façade elements, two typical
passive designs are briefly presented (Chan et al., 2010).
Trombe wall (double-skin façade):
it is a massive wall covered by an exterior glazing with an air channel in between. The function of
the glass is to trap solar radiation, while the wall absorbs and stores the solar energy and partially
transfers it to the interior room. The interior denser air enters the channel through a lower vent in
the wall; it is heated up, flows upward due to buoyancy effect and returns in the room through an
upper vent.
22
Solar chimney:
it is a thermo-syphoning air channel designed to improve ventilation stack effect by maximizing
solar gain, consequently increasing the difference between indoor and outdoor air temperature
(Khanal and Lei, 2011). In a cold or moderate climate, when the outdoor temperature is lower
than the indoor temperature, a solar chimney converts thermal energy in kinetic energy of air
movements. The thermal buoyancy driving mechanism is influenced by the geometry and the tilt
angle of the device.
This thesis deals mainly with the study of cross-ventilation effects. As mentioned, this technique is
implemented through the installation of ventilation openings on opposite building façades. In this regard,
a very recent study is cited. The research of Cheng et al. (2016) investigates the consequences of the
implementation of a natural cross-ventilation system in a large gymnasium (63.2m in depth, 147.8m in
length, maximum height 14.3m), currently equipped with an hybrid ventilation system. IES-VE is the
simulation software used for the thermal and airflow modelling. The study concludes that the net opening
size is a crucial factor that determines the airflow rate available for natural ventilation scopes. Moreover,
they verified that uniformity of the opening distribution positively affects the cross-ventilation efficiency
in a building with multiple inlets and outlets in opposite façades. Additionally, the study recognizes that an
appropriate design of the opening control strategy reduce building overheating and overcooling problems
more effectively than changes in building architecture.
Cross ventilation is a simple solution. However, windows selection is a fundamental and studied aspect of
the natural ventilation design process (Gao and Lee, 2010). Considering the site-specific climatic
limitations, window choice must be carefully evaluated. Roetzel et al. (2010) provide an overview on the
proprieties of different window opening types (fig. 14).
Figure 14. Window opening types. Source: Roetzel et al. (2010)
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3.2 Thermal comfort
The tendency of the HVAC industry is to maintain constant indoor temperature inside buildins, aiming to
satisfy the largest number of people. However, there are many factors that concur in the comfort
definition and there is not a temperature that will content all the occupants of a certain space (Santamouris
and Wouters 2006).
A person that function without involuntary stress from feeling too warm or too cold, from smelling
objectionable odours, or from having irritated eyes, nose, or throat is experiencing a condition of general
comfort. The comfort determinants include thermal, atmospheric, visual and acoustical aspects (Cain
2002). The different features of the indoor environment are interrelated and building occupants, to a
certain extent, are able to balance the good elements against the bad ones to perform a global evaluation
(Centnerová and Boerstra, 2010).
Specifically, according to the standard ASHRAE 55-2010 (ASHRAE 55, 2010), thermal comfort is defined
as the state of mind that expresses satisfaction with the thermal environment and is assessed by a
subjective evaluation. Therefore, thermal sensation is a crucial aspect of the comfort perception and
depends on different parameters (Allard 2002):
physical, as air temperature, air relative humidity and local air velocity;
physiological, as age, sex and particular characteristic of the occupants;
external, as human activity, clothing and social conditions.
Moreover, building users have different expectations and different abilities to adjust to the surrounding
thermal environment; their recent thermal history has an impact on their comfort perception; their cultural
background governs their reaction to the perceived discomfort and affects the evaluation of the
importance of thermal comfort itself (Harriman and Lstiburek, 2009).
Overall, the conditions that define an environment as satisfactory are dependent on several physiological
and psychological factors, which influence people differently.
Standards and models have been statistically elaborated to evaluate the thermal comfort of existing
buildings or to support the design stage of new ones. They are based on laboratory and field data. In this
study, the sports hall thermal environment has been assessed through the standards UNE-EN ISO 7730
(AENOR 2006), UNE-EN 15251 (AENOR 2008a), UNE-EN ISO 7933 (AENOR 2005), UNE-EN
12515 (AENOR 1997) and ASHRAE 55-2010.
Standards provide also recommendations about local thermal discomfort phenomena as asymmetrical
thermal radiation, draft, vertical air temperature difference and warm or cold floor.
The following sections are devoted to the description of the adopted models.
3.2.1 Predicted mean vote
The Predicted Mean Vote (PMV) is one of the most recognized thermal comfort model. It is related to
the Fanger’s model, based on thermoregulation and heat balance theories, according to which the human
body balances between the heat lost through the skin and respiration, and the heat produced by the
metabolism, implementing physiological processes (Orosa Garcia 2010).
The heat balance of the human body can be expressed through the following equation (eq. 6):
𝑀 − 𝑊 = (𝐶 + 𝑅 + 𝐸𝑠𝑘) + (𝐶𝑟𝑒𝑠 + 𝐸𝑟𝑒𝑠) + (𝑆𝑠𝑘 + 𝑆𝑐𝑟) (eq. 6)
24
Where:
M - rate of metabolic heat production
W - rate of mechanical work accomplished
C+R - sensible heat loss from skin
Cres - rate of convective heat loss from respiration
Eres - rate of evaporative heat loss from respiration
Ssk - rate of heat storage in skin compartment
Scr - rate of heat storage in core compartment
The analysis of the terms that compose the heat balance equation allows to identify the six parameters that
define the thermal status of human body, classifiable in personal and environmental factors:
activity
clothing
air temperature
air velocity
relative humidity
mean radiant temperature
According to Fanger’s approach, thermal sensation can be defined determining the deviation between the
actual condition of the body and the optimum comfort level (condition of neutrality). The PMV index is
the tool necessary to perform this comparison. Fanger developed it to study the results of a set of
experiments conducted with 1300 subjects in stable conditions in climate chambers. It has been then
normalized in the UNE-EN ISO 7730 standard. Fanger’s theory assumptions are reported below:
a) the “hot” or “cold” sensations are proportional to the thermal load (𝑀 − 𝑊), namely the difference
between thermal the power generated inside the human body and the thermal power dispersed by the
subject who is in well-being condition (considering the skin temperature and the sweat rate) performing a
specific activity;
b) there is a relation between the PMV index, the thermal sensation felt by an average individual and
expressed as a vote on a 7-point scale, and the thermal load.
The 7-point bipolar scale according which the PMV is defined is reported in table 11.
Table 11. Thermal sensation scale. Source: self-elaboration based on Orosa Garcia (2010)
PMV Thermal sensation
-3 Hot
-2 Warm
-1 Slightly warm
0 Neutral
+1 Slightly cool
+2 Cold
+3 Very cold
The PMV index can be evaluated according to the equation 7, which involves the 6 personal and
environmental variables listed above (Orosa Garcia 2010).
personal factors
environmental factors (microclimate parameters)
25
𝑃𝑀𝑉 = (0.303𝑒𝑥𝑝−0.0036 𝑀 + 0.028) ∗ {(𝑀 − 𝑊) − 3.05 ∗ 10−3 ∗ [5733 − 6.99(𝑀 − 𝑊) − 𝑝𝑎] −
0.42[(𝑀 − 𝑊) − 58.15] ∗ 1.7 ∗ 10−5𝑀(5867 − 𝑝𝑎) − 0.0014𝑀(34 − 𝑡𝑎) − 3.96 ∗ 10−8𝑓𝑐𝑙[(𝑡𝑐𝑙 +
273)4 − (𝑡𝑟 + 273)4] + 𝑓𝑐𝑙 ∗ ℎ𝑐 ∗ (𝑡𝑐𝑙 ± 𝑡𝑎)} (eq. 7)
Where:
pa - partial vapour water pressure
tr - mean radiant temperature
fcl - ratio of clothed surface area to nude surface area
hc - convective heat transfer coefficient
tcl - clothing surface temperature
In other words, the PMV index coincide to the vote of an average individual (precisely the average of the
votes expressed by a large number of people placed in predetermined temperature and humidity
conditions) expressed to evaluate the perceived subjective thermal sensation.
The condition of thermal neutrality corresponds to -0.5 < PMV < 0.5. However, even if PMV results null,
the votes of individuals considered separately have a certain dispersion around zero. For this reason, the
Predicted Percent of Dissatisfied (PPD) index is introduced. The PPD is calculated from PMV (eq. 8 and
fig.15) and predicts the percentage of people who are likely to be dissatisfied with a given thermal
environment, namely the percentage of the people who felt more slightly warm or slightly cold
(Djongyang et al., 2010).
𝑃𝑃𝐷 = 100 − 95𝑒−𝑛 (eq. 8) where
𝑛 = 0.03353𝑃𝑀𝑉4 + 0.2179𝑃𝑀𝑉2 (eq. 8.1)
Figure 15. Relationship PMV versus PPD. Source: Djongyang et al. (2010)
26
3.2.2 Adaptive model
The adaptive model has been elaborated to take into account the natural process of adaptation that users
perform assessing the thermal perception of an occupied building (Djongyang et al., 2010).
Thermal adaptive model derives from field studies. The term adaptation is referred to behavioural,
physiological and psychological mechanisms implemented to fit the indoor climate to personal
requirements (de Dear et al., 1997) (fig.16). It has been found that the evaluation of physical and personal
factors is not sufficient to accurately predict thermal sensation. This is especially true in context where
people can interact with the surrounding environment. Several studies show that in natural ventilated
buildings the occupants prefer a wider range of thermal conditions and variable indoor air temperature,
according to the outdoor climate parameters and to daily and seasonal climate changes. Conversely,
Fordham (2000) points out that the massive introduction of air conditioning systems reduces people’s
awareness and, enabling any temperature to be chosen, removes the need to understand what, for
example, can be defined “too hot”.
According to the adaptive principle, building users are considered active subjects. This means that when a
discomfort condition occurs, they are able to react and restore their comfort status undertaking a series of
actions (Rupp et al., 2015). From the adaptive point of view, comfort should be intended as a measure of
how successful those actions have been (Nicol et al., 2007).
The ASHRAE 55-2010 and UNE-EN 15251 standards recognize the thermal adaptation phenomenon
and provide a methodology to be applied in the study of naturally ventilated environment.
The application of the proposed thermal adaptive comfort procedure requires the introduction of an
additional parameter: the operative temperature (𝑇𝑜𝑝) defined as “a uniform temperature of a radiantly black
enclosure in which an occupant would exchange the same amount of heat by radiation and convection as in the actual non
uniform environment” (Kazkaz and Pavelek, 2013). 𝑇𝑜𝑝 correlates air temperature, mean radiant temperature
and air velocity according to the expression reported in the UNE-EN ISO 7730 standard (eq. 9):
𝑇𝑜𝑝 = 𝑇𝑎 ∗ 𝐴′ + 𝑇𝑟𝑚 ∗ 𝐵 (eq. 9)
where 𝐴′ and 𝐵 are function of the air velocity, as in table 12.
Figure 16. Thermal adaptive process. The components of adaptation to indoor climate. Source: de Dear et al. (1997)
27
Table 12. Coefficients for the calculation of Top depended on air velocity
Va < 0.2 m/s 0.2 < Va < 0.6 m/s Va > 0.6 m/s
𝑨′ 0.5 0.6 0.7 𝑩 0.5 0.4 0.3
The adaptive model allows the definition of an acceptable indoor temperature range. A relationship
between the optimal thermal indoor conditions and the exterior climate is established. This is a key aspect
that clearly differentiate the adaptive approach from the PMV model. In this regard, it should be make a
clarification. As it is possible to observe in the figure 17, the mean monthly outdoor air temperature is
used as reference exterior temperature. Its value, according to the ASHRAE 55-2010 standard, is
calculated as the arithmetic average of mean daily minimum and mean daily maximum outdoor
temperatures:
𝑇𝑎(𝑜𝑢𝑡) =𝑇𝑚𝑎𝑥 + 𝑇𝑚𝑖𝑛
2
The same parameter in the UNE-EN 15251 standard is calculated as an exponentially-weighted running
mean temperature:
𝜃𝑒𝑎 =𝜃𝑑𝑎−1+0.8∗𝜃𝑑𝑎−2+0.6∗𝜃𝑑𝑎−3+0.5∗𝜃𝑑𝑎 −4+0.3∗𝜃𝑑𝑎−6+0.2∗𝜃𝑑𝑎−7
3.8 (eq. 11)
where
𝜃𝑑𝑎 = ∑ 𝑡𝑚ℎ𝑟1𝑛=24 /24, the daily average exterior temperature; it is an average of the hourly average
outside temperature for one day (24h).
Figure 17. Acceptable operative temperature ranges. 90% acceptability limits = 90% of the occupants experience a comfort condition; 80% acceptability limits = 80% of the occupants
experience a comfort condition. Source: ASHRAE 55-2010 (2010)
(eq. 10)
)
28
Consequently, there are two different expressions to define the optimal operative temperature and the
correspondent indoor temperature acceptability range:
Table 13. Adaptive model parameters according to the ASHRAE-55 and EN UNE 15251 standards
ASHRAE 55-2010 EN-UNE 15251
TopOPTIMAL 𝑡𝑜𝑝 𝑜𝑝𝑡 = 0.31 ∗ 𝑡𝑎 𝑜𝑢𝑡 + 17.8 𝜃𝑜𝑝 𝑜𝑝𝑡 = 0.33 ∗ 𝜃𝑒𝑎 + 18.8
Acceptability 90% 80%
Category
I II III
𝑡𝑜𝑝 𝑜𝑝𝑡 ± 5 𝑡𝑜𝑝 𝑜𝑝𝑡 ± 7 𝜃𝑜𝑝 𝑜𝑝𝑡 ± 2 𝜃𝑜𝑝 𝑜𝑝𝑡 ± 3 𝜃𝑜𝑝 𝑜𝑝𝑡 ± 4
29
3.2.3 Required sweat rate
For the analytic determination of the thermal stress, the UNE-EN ISO 7933 and the UNE-EN 12515
standards are applied. The adopted model is based on the calculation of the heat exchanged between a
standard person and the environment. It is assumed that the heat is transferred through convection,
radiation and respiratory heat loss. The model is related to a rational/analytic index defined as Required
Sweat Rate (SWreq). The SWreq, derived from the heat balance equation, predicts the sweat rate necessary
to facilitate the evaporation required to maintain null the heat storage in the body (Bethea and Parsons,
2002). The methodology suggested in the standards is graphically summarized (fig.18)
As it is possible to see in figure 18, different parameters, regarding interior microclimate conditions as well
as personal factors, have to be implemented in the model. The interpretation of the results (outputs) aims
to determine the Duration Limited Exposure (DLE), namely the acceptable period of work that can be
performed in the evaluated environment. The DLE is function of maximum values of body heat storage
(Qmax) and water loss (Dmax). The DLE calculation considers as well the limits imposed for skin
wettedness (Wmax). Specifically, the results are interpreted according to two subcategories (Malchaire et al.,
2000):
warning level: there is no risk for any subject in good health performing the considered activity;
danger level: there could be risk for certain subjects, although in good health, performing the
considered activity.
Figure 18. Graphical description of the Required Sweat Rate model. Source: self-elaboration based on Luna Mendaza (1994)
OUTPUT SWreq
MODEL
INTERPRETATION
State of acclimatitation
Acclimatised and unacclimatised
Alarm and Danger Criteria
Predicted Sweat Rate
Duration Limiting Exposure (DLE)
INPUT
Air temperature (°C)
Radiant temperature (°C)
Wet bulb temperature (°C)
Air movements (m/s)
Metabolic rate (W/m2)
Mean radiant temperature (°C)
Partial vapour pressure (kPa)
Area of body exposed (Ar/Adu)
Clothing insulation (clo)
Mean skin temperature
Max evaporative rate
Required evaporation rate (Ereq)
Required Sweat rate (SWreq)
30
3.2.4 Givoni diagram
The bioclimatic diagram proposed by Givoni predicts the indoor thermal-hygrometric comfort state
according to the external prevailing climatic conditions. Bioclimatic charts are useful tools to identified the
best building passive thermal design strategies for a specific location. The definition of the Givoni building
bioclimatic chart (BBCC) is based on the linear relationship between the temperature amplitude and vapor
pressure of the outdoor air (Al-Azri et al. 2012). In the Givoni chart interior and exterior parameters are
introduced in a psychometric diagram, that graphically representing the relation between temperature and
air moisture content, allows to easily identify the comfort zone and its extension (La Roche 2011). The
diagram is organized in five different zones. The winter comfort zone results wider than the summer one,
assuming that the clothing and the metabolic activity that describe the building users are higher during the
coold season.
The Givoni diagram elaborated for the comfort analysis of the sports hall where the measurements
campaign has been performed, is reported in section 11.1.2
3.3 Indoor Air quality
Since ancient times natural ventilation contributed to satisfy building occupants demand of control on
acceptable indoor temperature and humidity levels. This aspect has been briefly discussed in section 3.1 of
this work.
However, other complementary needs arose along the human history, as the desire to eliminate
disagreeable contaminants from the occupied spaces. The ancient Egyptians realized that stones carvers
working inside were more subject to respiratory distress than people working outdoor and attributed the
phenomenon to the indoor high level of dust. In the Middle Ages people stated to link the transmission of
diseases to the density of occupation of common areas. In 1777, Lavoisier concluded that excess of CO2
causes sensation of stuffiness and so called bad air. In 1836, Thomas Tredgold published the first
estimation of the minimum quantity of ventilating air needed to ensure comfort (Janssen 1999).
Considering the fact that humans spend more than 80% of their lifetime inside close environments
(Norhidayah et al., 2013), it is undeniable that indoor comfort deserves thorough investigation. Many
studies have been focused on indoor pollutant measurements in residences, offices, restaurants and
shopping malls. While few researches can be found in literature regarding the evaluation of indoor
contaminants in large enclosures as sports halls. (Junker et al., 2000; Alves et al., 2013)
A poor indoor air quality can affect dramatically building habitability. Today it is increasingly frequent that
occupants exhibit symptoms of sick building syndrome (SBS) that lead to experience irritation, discomfort
or ill health (Allard 2002). It results that, in general, naturally ventilated buildings have fewer symptomatic
occupants than air-conditioned ones (Burge 2004). Health issues have increased in parallel with the wide
use of HVAC systems. This phenomenon often is related to the fact that ventilation ducts are dirty and
filters not changed, increasing contaminants that are recirculated into the occupied spaces (Clausen 2004).
The expression indoor air quality (IAQ) refers to the amounts of contaminants present in the indoor air.
Undesired emissions are caused by different sources. The users produce bio-effluents; the furniture, the
equipment, the internal partitions, surface paint and decorative pieces release chemical particles in the air.
Other common pollutants are fungi and micro-organisms (Chenari et al., 2016).
According to the UNE-EN 15251 standard, air quality can be evaluated referring to CO2 indoor
concentration. Normally, for ordinary building, the reached CO2 concentration levels are not harmful for
humans. However, CO2 concentration is a useful indicator of the contaminants produced by the human
body (Kleiven 2003). All people are CO2 sources, as a results of their metabolism. The CO2 emission rate
is not constant: depends on the type of person and on the performed activity level. Pre-defining a
31
maximum acceptable concentration level of a certain pollutant and identifying the dominant contaminant
source, it is possible to evaluate the require ventilation rate. Practically, the pollution decreases
exponentially increasing the air flow rate (fig.19) (Allard 2002).
Figure 19. Ventilation and air quality. Source: Allard (2002)
32
4 Methodology
The methodology according to which this research has been realized, includes different steps.
First, in order to complement the available environmental comfort performance data about typical
Spanish sports halls (section 2.1), a field measurements campaign has been conducted in an existing sports
facility. Information regarding occupation patterns and environmental indoor quality have been collected
through field measurements. Thermal microclimate parameters, as indoor air temperature at different
heights, radiant temperature, air velocity, relative humidity and air quality indicators, as CO2 concentration,
have been measured during different usage conditions of the sports hall. Additionally, the appropriate
clothing insulation and metabolic activity profiles of the users have been estimated. At the same time of
the measurements campaign, the subjective perception of the occupants has been investigated through a
questionnaire survey. Following the procedures described in ASHRAE 55-2010 and UNE-EN 15251, the
adaptive and Fanger thermal comfort models have been applied to evaluate the internal comfort
conditions. Secondly, a selection of energy efficiency and renewable energy integration strategies is
introduced. The base case sports hall is identified following the technical indications provided by the
Catalan sports council (Consell Català de l’Esport 2005) concerning a so-called triple sports hall (PAV3). A
triple sports halls is a sports facility equipped with a playing field that can be divided in three transversal
spaces, increasing its versatility. When the base case sports hall 3D geometry is modelled in Google Sketch
Up, it is introduced in the simulation by a 3D model, realized through the plugin Trnsys3D. The energy
efficiency measures are then tested using the dynamic simulation tool TRNSYS. Within the proposed n-
ZEB strategies, natural ventilation is studied more in detail in order to estimate its impact on thermal
comfort, air quality and energy needs. The contribution of the designed natural ventilation system is
assessed through TRNFLOW, the extension realized to integrate the airflow and pollutant transport
model COMIS into the multizone building thermal model of TRNSYS and based on air mass
conservation laws (Weber et al. 2003). Therefore, the ventilation behaviour and the ventilation effects on
the building indoor conditions are investigated. The implementation of renewable energy systems,
specifically the potential contribution of the installation of a photovoltaic system, is estimated through the
Google Sketch Up plug-in Skelion and the type 94 of TRNSYS. Finally, the economic evaluation of the
studied cases is realized implementing the cost-optimal methodology, consistence with the guidelines
provided by the European Union (IEA 2014).
The detailed description of each phase of the research is reported in the following sections. Moreover, a
scheme of the implemented methodology is reported in figure 20.
Figure 20. Research methodology
33
5 Measurement campaign
The field measurement campaign has been realized in the “Poliesportiu Pla Del Bon Aire” located in
Terrassa (Barcelona) and currently not equipped with a ventilation system neither a heating system. The
main goal is to evaluate the indoor environmental quality (IEQ), the thermal condition and the perception
of the users, players and audience, of the sports facility. Therefore, thermal microclimate parameters and
air quality indicators have been monitored.
The measurements has been performed along two days, 12/03/2016 and 13/03/2016. The first day, the
instrumentation were installed, compromising between quality of measurements, equipment safety and
reduction of the interaction of the building users. The measurements equipment named Tower 1 and Tower
2 include different sensors, while the equipment named Sensor 1 and Sensor 2 are more compact devices
(fig.20).
Measuring devices were placed on the playing field floor (Tower 1 and Tower 2) and on higher level (Sensor 1
and Sensor 2), in different locations of the sports hall, as shown in figure 21 and in figure 22.
The environmental parameters assessed during the measurements campaign are summarized in table 14.
All the data have been recorded with 3 minutes interval. Measurements were carried out when sports hall
was empty as well as fully occupied. The matches took place during the second day of measurements
between 09:30 and 13:45 in the morning and between 16:00 and 21:30 in the evening. The different
occupation condition were registered. Table 15 summarizes the occupation pattern registered in the sports
hall during the day of measurements.
Figure 21. Measurements devices: left, Tower 1 and Tower 2; right, Sensor 1 and Sensor 2
34
Table 14. Measurements configuration
Measurements and position Tower 1 Sensor 1 Tower 2 Sensor 2
Air temperature 0.1 m x x 0.6 m x x 1.1 m x x 1.4 m x x 1.7 m x x 2.8 m x x
Globe temperature 1.4 m x x Relative humidity 1.4 m x x
2.8 m x x Air velocity 1.4 m x CO2 concentration 1.4 m x x
2.8 m x x Dew point temperature 2.8 m x x
Hours: (3 minutes steps)
12/03/2016 20:15-00:00 20:11-00:00 20:36-00:00 20:45-00:00 13/03/2016 00:00-21:51 00:00-21:47 00:00-21:39 00:00-21:39
Table 15. Occupation of the sports hall
Hours 07:30 08:30 10:30 12:30 16:30 18:30 19:30 21:30
Occupation 10 90 100 180 75 115 330 330
To have a complete description of the actual thermal performance of the sports hall, a survey related to
indoor air perception was conducted among the audience (Annex 1). The survey has been performed at
different hours of the day. The aim of the survey was to collect information about the thermal sensations
experienced by the audience, to then compare them to the measurements results.
Figure 22. Placement of the measurements devices in the sports hall
AUDIENCE SEATS
35
5.1 Assumptions and parameters
In order to calculate the thermal comfort index PMV, as well as to apply the adaptive comfort model,
some parameters have to be defined:
metabolic rate (Met): according to the standard ASHRAE 55-2010, different values have been
identified for the players and the audience:
Table 16. Metabolic rate
Activity Met
Players Basketball 6.3
Audience Seated, heavy limb movement 2.2
clothing insulation (CLO): as reported in the standard ASHRAE 55-2010:
Table 17. Clothing insulation
Garments CLO
Players Walking shorts, short sleeve shirt 0.36
Audience Morning Trousers, long-sleeve shirt plus long-sleeve sweater 1.01 Evening Trousers, long-sleeve shirt plus long-sleeve sweater 1.01
The value of clothing insulation relative to the audience has been determined taking into account the
answers received in the proposed survey, as shown in table 18.
Table 18. Survey answers. Clothing description
Thermal comfort survey answers
Morning Evening
1. Shorts and short-sleeved shirt 3
2. Throusers and short-sleeved shirt 2 4
3. Throusers and long-sleeved shirt 11 5
4. Throusers and jersey 13 7
5. (3) + jacket 3 2
6. (3) + jersey and interior shirt 1 2
7. Knee-length skirt and short-sleeved shirt
8. Knee-length skirt and long-sleeved shirt 1
9. Knee-length skirt and jersey
10. (7) + jersey
11. (7) + jacket
12. Ankle-length skirt, long-sleeved shirt and jacket
mean radiant temperature: the method provided by the UNE-EN ISO 7726 (AENOR 2002b)
standard has been used to calculate this parameter that cannot be directly measured. The method
is briefly explained. The desired parameter must be extrapolated from another variable, the globe
temperature. The used global thermometer is normalized (diameter of 0.15 m and balloon
emissivity of 0.95). The relative equations are:
36
- natural convection:
𝑇𝑟𝑚 = [(𝑇𝑔 + 273)4
+ 0.4 ∗ 108 ∗ |𝑇𝑔 − 𝑇𝑎|1
4 ∗ (𝑇𝑔 − 𝑇𝑎)]1/4
− 273 (eq. 12)
- forced convection:
𝑇𝑟𝑚 = [(𝑇𝑔 + 273)4
+ 2.5 ∗ 108 ∗ 𝑉𝑎0.6 ∗ (𝑇𝑔 − 𝑇𝑎)]
1/4− 273 (eq. 13)
The convection regime is determined by the highest value of the heat transfer coefficients
calculated as follow:
- natural convection
ℎ = 1.4 ∗ (∆𝑇
𝐷)
1/4
- forced convection
ℎ = 6.3 ∗ (𝑉𝑎
0.6
𝐷0.4 )
where ∆𝑇 = 𝑇𝑎 − 𝑇𝑔 and 𝐷 is the global thermometer diameter.
The mean radiant temperature is needed for the PMV index calculation (section 3.2.1).
The sports hall comfort study required additional assumptions:
only one air velocity sensor was available, therefore the air velocity measured through Tower 1 is
assumed to be equal in all the measurements areas;
only the equipment installed in Tower 2 for the air quality evaluation worked properly, therefore
the CO2 concentration relative to Tower 1 is assumed to be equal to the value measured through
Tower 2;
the comfort investigation is performed only regarding the occupation periods, namely between
9:30 and 21:30 of 13/03/2016;
the exterior CO2 concentration is assumed to be equal to the lower concentration registered
through the indoor sensors during the night (451 ppm at 05:36).
It was not possible to install a weather station to collect data regarding the exterior weather conditions.
The needed external parameters, as air temperature and humidity, have been extrapolated from the
database provided by the Meteorological Service of Catalonia (Generalitat de Catalunya 2016) regarding
the observation conducted every half an hour in the meteorological station of Sabadell - Parc Agrari,
located at 10 km from the studied sports hall. The information about the evolution of the average
monthly temperature along the years in Terrassa, that as explained in section 3.2.2 are needed in the
implementation of the adaptive model, have been provided by InfoMet (Universitat de Barcelona -
Departament d'Astronomia i Meteorologia 2016), a database realized by Department of Astronomy and
(eq. 14)
(eq. 15)
37
Meteorology at the University of Barcelona with the support of the Catalan Foundation for Research. The
average values relative to the two days of measurements are reported in table 19.
Table 19. Exterior weather parameters
12/03/2016 13/03/2016
Temperature Average 8°C 7.7°C Maximum 14.8°C 14.5°C Minimum 2.7°C 0.2°C
Average relative humidity 63% 64% Precipitation 0 mm 0 mm Maximum wind gust 25.9 km/h 32.8 km/h Average atmospheric pressure 1’020.5 hPa 1’019.8 hPa Global solar irradiation 18.9 MJ/m2 18 MJ/m2
Finally, the infiltration of the building has been evaluated applying the CO2 tracer gas concentration decay
method described by Cui et al. (2015). It results that the building infiltration correspond to an ACH value
of 0.27h-1.
5.2 Data elaboration
After the data acquisition phase, the measured internal conditions have been analyzed in combination with
the weather variable, the results of the survey and the assumed parameters.
The graphic elaboration of the collected data, regarding the microclimate indoor parameters recorded
during the measurements campaign, are reported below.
The indoor temperatures start to increase around 9:00 in the morning, following the behaviour of the
external temperature. Observing the interior temperatures recorded by Tower 1, it is possible to notice that
the maximum value of 24.5°C is registered by the sensor at 1.4 m at 16:15. Similarly, the sensors of Tower 2
registered the maximum temperature of 23.9°C at 16:18, but at higher altitude (1.7 m) (fig.23).
In relation to the indoor relative humidity, the registered values and the correspondent exterior
measurements are presented in figure 22. The maximum relative humidity value is registered through
Tower 1 during the day at 14:09 (43.6%) and in the evening at 21:30 (62.5%). Tower 1 measured also a
minimum value of 33.7% at 15.24, when the sports hall was not occupied (fig.24).
Figure 25 represents the evolution of the air velocity, measured through a specific sensor located on Tower
2. The minimum registered air velocity value corresponds to 0.08 m/s, the maximum is 0.28 m/s. On
average, the air velocity during the measurements campaign was of 0.17 m/s. However, considering the
high sensitivity of the measurements instrument, likely the collected data have been affected by the
proximity of the audience, especially during the hours of maximum occupancy.
The last graph (fig.26) reports the measured interior CO2 concentration. The maximum CO2
concentration regarding the morning measurements was registered through Tower 2 at 13:39 (1268 ppm);
while at the 21:30 the concentration reached the value of 2127 ppm. It is possible to notice that a
significant decrease of CO2 concentration occurs around 15:00 (the daily minimum concentration is 706
ppm, registered at 15:15), when the sports hall was empty and the matches suspended.
38
002:00:00 002:04:48 002:09:36 002:14:24 002:19:12
0
5
10
15
20
25
30
Tem
pera
ture
(°C
)
T_0.1m T_0.6m T_1.1m T_1.4m T_1.7m T_2.8m T_ext
Tower 2
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
10
15
20
25
Tem
pera
ture
(°C
)
T_0.1m T_0.6m T_1.1m T_1.4m T_1.7m
Tower 1
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
10
15
20
25
T_0.1m T_0.6m T_1.1m T_1.4m T_1.7m
Tem
pera
ture
(°C
)
Tower 2
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
0
5
10
15
20
25
30
Tem
pera
ture
(°C
)
T_0.1m T_0.6m T_1.1m T_1.4m T_1.7m T_2.8m T_ext
Tower 1
Figure 23. Air temperature measurements
39
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
30
40
50
60
70
80
90
Rela
tive H
um
idit
y (
%)
HR tower 1 HR tower 2 HR_ext
Relative Humidity
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
400
600
800
1000
1200
1400
1600
1800
2000
2200
CO
2 (
pp
m)
sensor 1 tower 2
CO2 concentration
001:00:00 002:04:48 002:09:36 002:14:24 002:19:120,05
0,10
0,15
0,20
0,25
0,30
Air
ve
loc
ity
(m
/s)
Figure 25. Air velocity measurements
Figure 24. Relative Humidity measurements
Figure 26. CO2 concentration measurements
40
6 Proposed n-ZEB strategies
As described in section 2.1, sports halls are characterized by very specific energy needs. With the goal of
fulfill the energy needs of this particular kind of installation satisfying the users comfort requirements and
achieving a significant reduction of the primary energy use, appropriate n-ZEB strategies have been
selected. The selection occurred in the light of the climatic conditions of the site and of the type of use
that characterize the investigated sports facility. Consequently, considering the solutions presented in
section 2.2, implemented in the already existing net zero energy sports buildings, the data collected during
the measurements campaign and the guideline available regarding energy efficient sports halls, (ICAEN
2012, Guía de Eficiencia Energética en Instalaciones Deportivas 2008), a suitable set of passive
approaches, energy efficiency measures and renewable energy systems have been identified (tab.20).
Table 20. Proposed n-ZEB strategies
Measures Implementation Objective
Pas
sive
str
ate
gie
s an
d c
on
tro
l
Thermal behavior
Selection of building materials to ensure low
thermal transmittance of the envelope
Optimization of the ratio opaque components/
windows of the façade according to the building
orientation
Installation of shading device in the South-East
façade, dimensioned to take advantage of
natural light during winter and to reduce solar
radiation during summer
ensure good
thermal
insulation
use solar
gains
avoid risk of
overheating
Natural light
Design of the South-East façade to maximize the
contribution of natural light
Installation of diffuses light sources
Installation of skylight devices
ensure visual
comfort
avoid glare
Natural ventilation
Definition of control system
Design independently from the natural light
system
Nigh ventilation
ensure
thermal
comfort of
the users
ensure good
air quality
Re
ne
wab
le
en
erg
y sy
ste
m
PV installation
Design of the façades and the roof to allow the
installation of PV panels
Study of the optimal roof slope and orientation
to maximize the energy production
reduce
energy costs
reduce CO2
emissions
Act
ive
sys
tem
Systems
efficiency
Artificial
light
Installation of LED lamps
Regulation with control system reduction of
energy costs Heating
system
Sizing according to the heating demand
Evaluation of heat pump/condensing boiler
installation
Overall, the presented building concepts and energy approaches aim to achieve a significant reduction in
the energy demand due to the mechanical systems typically installed in a sports hall (lighting, ventilation,
heating and cooling), without compromising indoor comfort and air quality conditions. Specifically, this
study, within the set of measures presented in the table 20, evaluates in details which is the effect of the
implementation of natural ventilation on the sports hall energy performance toward n-ZEB standards. a
natural ventilation system has been designed and its effectiveness has been energetically and economically
assessed.
41
7 Base case description
The indoor comfort condition of a building derives from the interaction of different aspects:
environmental factors, as the external climate; building factors, as shape and construction materials;
occupants related factor, as internal gains (Huang et al., 2015)
This section describes in detail the base case study and the related aspects listed above.
7.1 The triple sports hall
The starting point of the base case building definition is, as introduced in section 4, the technical
document provided by the Catalan sports council regarding the triple sports halls characterization and
intended as a guide for the building designer (Consell Català de l’Esport 2005). It results that 133 on 564
Catalan sports installations are triple sports halls. Therefore, PAV3 is a representative building typology.
The main features of a triple sports halls (fig.27), as reported in the technical report, are:
dimension of the playing field: 45 m x 27 m
minimum height: 8.5 m
maximum capacity: 300 people of audience and 168 players
minimum interior temperature: 14°C
minimum lighting: 200-400 lux
minimum ventilation rate: 2.5 dm3/sm2
orientation: the longitudinal axis should be oriented to the East-West direction; Southern
openings should be equipped with protection from direct incidence of sunlight
The document elaborated by the Catalan sports council does not mention specific requirements about
energy usage.
It must be taken into account that the mentioned report includes structural, hygienic and of maintenance
indications regarding all the spaces forming part of the sports hall, as locker rooms, bathrooms and
warehouses. However, in this thesis only the space relative to the playing field and the seats where the
audience is allocated, are examined. Therefore, the calculation regarding DHW consumption and the
specific comfort condition that must be guaranteed in the locker rooms are not performed.
Moreover, it is important to highlight that the entire research is based on a real project developed, in
collaboration with IREC, by the municipality of Sant Andreu de Llavaneres (Ajuntament de SANT
ANDREU DE LLAVANERES 2015a, 2015b), 40 km away from Barcelona. The project regards the
construction of a new triple sports hall. The design includes eco design elements and aims to minimize the
building energy consumption. This clarification implies that this thesis has been developed respecting
some boundary conditions and does not involve the study of those parameter assumed as default, for
example building orientation.
Neither in the technical report redacted by the Sport Council nor in the original project, there are
recommendations about building airtightness. This means that there are not information regarding desired
building infiltration. It is defined infiltration the ventilation that occurs through adventitious openings
(Etheridge 2015). In buildings, some infiltration will always be present and an accurate evaluation of its
contribution is fundamental during the ventilation system design process to avoid risk of oversizing
(d’Ambrosio Alfano et al., 2012).
42
To define this important parameter, it is adopted the approach proposed by Florentzou et al. (2015). The
researchers suggest that “a reasonable and controlled infiltration is not the enemy of building energy performance”. The
results of their study confirm that in large spaces infiltration is almost sufficient to provide good air
quality. Consequently, the air tightness of the studied sports hall is considered equal to n50 = 2.6 h-1
According to UNE-EN 15242 (AENOR 2007), the considered value corresponds to a level of airtightness
medium. This choice is in sharp contrast with the trends occurring in the high efficiency building sector
and with the Passivehouse (Passive House Institute 2015) standard requirements that set a maximum of
n50 = 0.6 h-1. However, it is expected that the defined infiltration will not affect negatively the sports hall
thermal behavior. In this regard, the comparison can be made with the German and Norwegian
regulations, that specify a minimum airtightness requirement of n50 = 3 h-1 for non-residential natural
ventilated building (Erhorn-Kluttig et al., 2009). Taking into account that the abovementioned countries
are characterized by cold climate, the impact of the infiltration losses on heating energy use should result
very low in the Spanish context.
Figure 27. The triple Sports Hall. Source: Consell Català de l’Esport (2005)
27 m
43
7.2 Occupation patterns
Sports hall energy consumptions are closely related to the number of users of the installation (section 2.1).
For this reason, with the contribution of the data collected during the measurements campaign, realistic
profiles of the sports hall occupancy have been defined. Two main occupancy patterns are identified,
corresponding to weekdays and weekend. The information regarding the occupancy schedule are reported
in table 21.
Table 21. Sports hall occupation. (1° = Saturday; 2° = Sunday)
occupation
weekdays weekends
schedule 17-22 7-9 9-11 11-14 14-16 16-19 19-20 20-22
1° 2° 1° 2° 1° 2° 1° 2° 1° 2° 1° 2° 1° 2°
players 45 0 0 40 40 40 40 0 0 35 35 35 35 35 35 audience 20 8 10 40 50 48 60 8 10 40 50 64 80 200 300 total 65 8 10 80 90 88 100 8 10 75 85 99 115 235 335
7.3 Weather data
As outlined in the theoretical framework section (section 3), weather conditions have a fundamental
impact on the building thermal behavior and consequently on the selection of appropriate energy saving
strategies.
It is assumed that the studied sports hall is located in Spain, specifically in the Catalan city of Barcelona.
According to the Köppen Climate Classification system, Barcelona is characterized by a Subtropical-
Mediterranean climate (AEMET 2011). The climatograph elaborated from the information provided by
AEMET (2016) (extracted from the publication Guía resumida del clima en España 1981-2010), is reported in
figure 28. It results that annually the average temperature is 15.5°C, the maximum 19.2°C and the
minimum 11.7°C, while the average relative humidity is 70%.
Januar
y
Febru
ary
Mar
chApri
lM
ay
June
July
August
Sep
tem
ber
Oct
ober
Nove
mber
Dec
ember
5
10
15
20
25
30
Te
mp
era
ture
(°C
)
T_MAX T_MIN RH Sunny hours
0
20
40
60
80
RH
(%
)
150
200
250
300
Sh
Figure 28. Climatograph of Barcelona. Source: self-elaboration based on AEMET (2011)
44
The information on the wind characterization regard year 2015 and have been provided by “Servicio
Meteorológico de Cataluña (Generalitat de Catalunya 2016b)”. The prevalent wind direction results North-
West while the percentage of calm is 11.9% (fig. 29).
The weather condition of the chosen site are introduced in the building simulation through a data file in
typical meteorological year (TMY2s (NREL 2016)) format. The TMY2s are data sets of hourly values of
solar radiation and meteorological elements for a 1-year period. They represent typical rather than extreme
conditions.
Figure 29. Left: wind rose. Right: average wind velocity for each direction (m/s). Source: Servicio Meteorológico de Cataluña
45
7.4 3D geometry definition
The base case sports hall 3D geometry is defined through the modelling software Google Sketch Up,
respecting the technical requirements reported above.
The dimensions of the building are summarized in table 22.
Table 22. Sports Hall dimensions
Volume [m3] Area [m2]
Sports hall 13’618 1’485
Figure 30. Sports Hall 3D model
46
8 TRNSYS: building simulation
TRNSYS is the calculus tool used to perform the building simulation. TRNSYS is a transient resolution
software with a modular structure. It allows solving complex energy system problems subdividing them in
a series of smaller component (Kim et al., 2009). The sports hall geometry presented in the previous
section (section 7.4) is introduced in the simulation by a 3D model, using the plugin Trnsys3D for Google
SketchUp. Specifically, the thermal behavior of the building is modelled through type 56 component
(TRNSYS 17).
Natural ventilation is high dependent on climate and site specific characteristics. Therefore, there is not
“one set of determined criteria” applicable to every naturally ventilated building. In this context the modelling
tool as TRNSYS are extremely useful to predict and optimize the natural ventilation system performance
(Stephan et al., 2009).
8.1 Thermal behavior
The thermal characteristics of the selected opaque components of the envelope are reported in table 23,
while the thermal performance of the windows in table 24. The complete description of the opaque
components, as well as the windows description, are reported in Annex 2.
Table 23. Thermal performance of the construction elements
U – value (W/m2K)
Façade NE and SW 0.284
Façade SE and NW 0.296
Interior wall 0.304
Roof 0.284
Floor 1.366
Table 24. Thermal performance of the windows
Windows_lower level Windows_higher level Window 3_skylight
Frame Glazing Frame Glazing Frame Glazing
Composition
Aluminium
with thermal
break
Clear
double
glazing
6/16/6
Aluminium
with thermal
break
OKAPANE
(OKALUX GmbH
2016) with glass
fibre tissue, 16
mm, air 40 mm
Aluminium
with thermal
break
Double
glazing with
prismatic
lens
U–value
(W/m2K) 2.27 1.26 2.27 1.24 2.27 1.4
g – value (-) 0.368 0.335 0.589
Area frame
glazing (%) 15 85 5 95 5 95
47
It is important to draw attention to the fact that, as specified in table 20, the ventilation requirements of
the building are satisfied through a system designed independently from the natural light one. This means
that the windows and the skylight are not operable (they cannot be opened). They are designed to take
advantage of the illuminance and of the heat gains freely made available by the sun. They are conform to
esthetic needs and allow to establish a dialogue between the external and the internal environment.
U-value is a measure of thermal insulation performance of construction materials and building elements.
The thermal transmittance values considered in this study (except for the one relative to the ground floor
that must meet specific construction requirements considering the peculiar function of the building) are
significantly lower than the ones proposed by the Spanish Building regulation (CTE, Código Técnico de la
Edificación, 2013). The CTE sets in fact for the climatic zone of Barcelona (named C2) limits U-values of
0.73 W/m2K and 0.5 W/m2K, respectively for buildings façades and roof.
All the parameters summarized in the above mentioned tables are introduced in the TRNSYS simulation
(fig.31). The façades and the windows are in contact to the exterior environment.
In the simulated building, there is only an interior wall. The interior wall, mentioned in table 23, is located
in the North West direction and it is assumed to be in contact to the lockers room. The boundary
temperature for this partition wall is considered of 23°C or 18°C, respectively during the warm and cold
occupied period. While, the unoccupied periods are characterized by a boundary parameter evaluated as
average of the previous values and the exterior registered temperature. The ground temperature is
introduced according to the indication reported in the Guía técnica de condiciones climáticas exteriores de proyecto
redacted by ATECYR (2010) (𝑇𝑔𝑟𝑜𝑢𝑛𝑑 = 0.0068 ∗ 𝑇𝑎𝑖𝑟2 + 0.963 ∗ 𝑇𝑎𝑖𝑟 + 0.6865 [°𝐶]).
As it possible to see in figure 30, 14 skylights are placed on the building roof. The skylights contribution is
simulated according to the technical specification of Sunoptics ® - Lledó (2011).
Figure 31. TRNSYS building simulation. Building envelope characteristics
48
Additionally, it is clarified that the second row of windows represented in figure 30 are made of
OKAPANE, namely light diffusing insulation panels, introduced to reduce heat losses and take advantage
of daylight availability.
The thermal behavior of the building is also affected by the installation of a fix horizontal overhang
(length 38m and width 2m) that aims to prevent temperature increase during the warm season.
8.2 Internal gains
The internal gains of a building are formed by the release of sensible and latent heat from the indoor heat
sources. This study considers the contribution of the building occupants and of the lights appliances. The
internal gains are implemented in the simulation through the TRNSYS Gain Type Manager.
The total heat gain due to people occupancy is evaluated considering the performed activity (tab.16;
applied conversion factor 1 met= 58 W/m2) and taking into account the mean surface area of the human
body (approximately 1.8 m2 (ASHRAE 1994)). The sensible heat produced by the occupants depends on
their metabolic activity and on the indoor air temperature, according to the equation (Michaelsen and
Eiden, 2009):
��𝑠𝑒𝑛𝑠𝑖𝑏𝑙𝑒_𝑜𝑐𝑐𝑢𝑝𝑎𝑛𝑡
= 6.461927 + 0.946892 ∗ 𝑀𝐸𝑇 + 0.0000255737 ∗ 𝑀𝐸𝑇2 + 7.139322 ∗ 𝑇𝑎𝑖𝑟
− 0.0627909 ∗ 𝑇𝑎𝑖𝑟 ∗ 𝑀𝐸𝑇 − 0.19855 ∗ 𝑇𝑎𝑖𝑟2 + 0.000940018 ∗ 𝑇𝑎𝑖𝑟
2 ∗ 𝑀𝐸𝑇
− 0.00000149532 ∗ 𝑀𝐸𝑇2 ∗ 𝑇𝑎𝑖𝑟2
The total sensible heat produced by the users of the sports hall is considered 30% convective and the
remaining 70% radiative (ASHRAE 1993). Knowing the generated sensible heat, the latent contribution
can be extrapolated.
The artificial lights system is mounted at 13 meters high. It is composed of 30 led lamps consuming 276
W each, with luminous efficiency of 80% (Ortiz et al. 2015). The installed systems is designed to ensure
300 lux of indoor illuminance, following the recommendation of UNE-EN 12193 (AENOR 2012) for
sports activities as basket. Therefore, the contribution of the lights equipment to the internal heat load is
calculated in function on the natural light availability. Artificial lights are assumed to be ON when the
natural light provided by the 14 skylights placed on the building roof is lower than the required
illuminance level and the sports hall is occupied. The data, on monthly bases, regarding the daily average
sunlight availability are provided by an external collaborator and introduced as input in TRNSYS. The
resulting schedule of the assumed artificial light use is reported in figure 32.
Figure 32. Use of artificial lights schedule. 1 = lights ON if the sports hall is occupied (natural light <300 lux); 0 = lights OFF (natural light>300 lux). Source: self-elaboration based on data provided by an external collaborator
(eq. 16)
49
8.3 Natural ventilation
Natural ventilation has been investigated in detail. It is chosen as the main strategy to ensure optimal
indoor air quality condition and thermal comfort, avoiding the energy consumption due to mechanical
systems.
The thermal comfort is evaluate applying the adaptive comfort model. The comfort conditions are set
according to the limits defined in the standard UNE-EN 15251 and observing the requirements reported
in the document redact by the Catalan sports council. The interior optimal operative temperature (𝜃𝑜𝑝𝑜𝑝𝑡)
is calculated following the procedure proposed by the standard. In the TRNSYS Comfort Type Manager tool
the value of the audience metabolic rate (2.2), the audience clothing factor (considered 0.36 during the
warm season and 1.01 during the winter time) and the assumed relative air velocity are introduced as
inputs. The mean radiant temperature is a TRNSYS output as well as the indoor operative temperature.
CO2 indoor concentration (given as TRNFLOW output) is the parameter used to evaluate the indoor air
quality (table 25). The exterior CO2 concentration is considered 450 ppm.
Table 25. Building simulation: comfort parameters
Lower limit Upper limit Source
Operative temperature (°C) 𝜃𝑜𝑝𝑜𝑝𝑡 − 3 𝜃𝑜𝑝𝑜𝑝𝑡 + 3 UNE-EN 15251
Indoor temperature (°C) 14°C - Catalan sports council
CO2 concentration (ppm) - 𝐶𝑂2𝑒𝑥𝑡𝑒𝑟𝑖𝑜𝑟 + 750 UNE-EN 15251
As mentioned, cross-natural ventilation is modelled through TRNFLOW. Two identical openings (called
airlinks) are introduced in the opposite façades of the building, taking into account the prevalent wind
direction of the site (section 7.3). A large opening by definition is an internal or external opening that can
be characterized by two-way flow (Allard 2002). The characteristic of the openings are reported in table 26
(fig. 33).
Figure 33. TRNFLOW natural ventilation simulation
50
Table 26. Components of the simulated natural ventilation system
Opening Description Dimension
[m2] Position: high [m]
North-West façade Horizontal sliding 9 6.30 South-East façade Horizontal sliding 9 0.45
The TRNFLOW airflow model is based on a network model of the building (TRNFLOW 2009),
according to which the different nodes are linked by non linear conductances that model the airpath. For
the studied case this means that the North-West opening (airlink 1) relates (From-Node) the outdoor
conditions (external node) to (To-Node) the sports hall internal space (thermal airnode). While the opening in
the South-East façade (airlink 2) links (From-Node) the interior of the building (thermal airnode) to (To-Node)
the exterior environment (external node). The external nodes are defined introducing the wind pressure
coefficient values for each wind direction angle. The thermal node description consists in the airnode
dimensioning.
The wind pressure coefficient, the discharge coefficient and the wind velocity profile are introduced
according to the parameters reported in literature and in the TRNFLOW manual. The wind velocity
profile exponent is assumed α = 0.3; this values, equal to all directions, corresponds to a roughness class 3,
referred to a terrain located in “small city, suburb” (TRNFLOW 2009), suitable for the considered study
case assuming that a large installation, as the simulated sports hall, is not designed for a city center. The
wind pressure coefficient is a fundamental parameter to calculate ventilation rates in buildings (eq. 1).
However, as wind velocity is dependent upon the geographic region, terrain category, shielding and the
topographic location, wind pressure coefficients are dependent upon the building geometry and roof
pitch. In this study wall averaged Cp-values for low rise semi-shielded buildings (up to 3 storeys), with a
length to width ratio 2:1, are used. The reference values are provided by Orme et al. (1998). The discharge
coefficient is a parameters that refers to the configuration of the opening itself. Namely, it accounts for
the fact that different air flow characteristics could be obtained from different opening type (Vitooraporn
and Walaikanok, 2002). The discharge coefficient value for large opening is the ratio between the real flow
rate through the opening and the theoretical flow rate calculated with the Bernoulli equation (TRNFLOW
2009). In the sports hall simulation the default value for sliding window, Cd = 0.6, is implemented.
The desired infiltration (section 7.1) is simulated introducing cracks in the building envelope. Typically,
cracks are defined as openings with dimensions smaller than 10 mm (Allard 2002). The air leakages
associated to the two large openings and to the not operable windows in the façade (air leakages through
the skylights are neglected) are modelled defining the cracks length, equals to the entire perimeter of the
listed construction elements (179 m). The flow coefficient of the cracks must be defined as well. At this
scope, the conversion formula reported in UNE-EN 15242 is used:
𝑄50
𝑄1= 13.59
Equation 17 is valid for flow coefficient exponent 𝑛 = 0.667. 𝑄 indicates the air flow in [m3/s] at 50Pa
(𝑄50) and at 1Pa (𝑄1). Taking into account that
𝑄50 = 𝑛50∗𝑉𝑜𝑙𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔
3600
(eq. 18)
(eq. 17)
51
the resultant flow coefficient value per meter of crack length is 0.0048794 [kg/s/m at 1Pa].
The only examined pollutant inside the zone is CO2. The outside concentration is set to 450 ppm and
assumed constant for all the external nodes and directions. The occupants of the sports halls are
considered as CO2 source in proportion to their metabolic activity. Therefore, in the simulation the
contaminant exhalations from the audience accounts for 21.5 l/s per person while players are responsible
for 62.5 l/h per person (Demianiuk et al., 2010). The air velocity in the building is assumed equal to 0.25
m/s when the natural ventilation is not operating and of 0.5 m/s when the openings are open. The
selected values are in the range of acceptability considering that the recommended upper limit of indoor
air movement is usually 0.8 m/s (Allard 2002).
8.3.1 Control strategy
As mentioned, natural ventilation working principles depend on variable parameters as wind pressure and
temperature difference. Internal building requirements and occupation pattern are not constant as well.
Therefore, a control strategy is fundamental to ensure desired indoor conditions and natural ventilation
efficiency. The importance of control in reducing energy consumption has become evident also for energy
demanding solution as mechanical ventilation systems (Raja et al. 2001).
As reported in the section 3.2.2, users tend to accept wider comfort ranges when they can exert control on
the surrounding environment. However, manual control is not the most efficient solution for public
building occupied by more than one person (Allard 2002). Automatic control is considered more effective
for the studied sports hall. Automatic control systems for natural ventilation usually include sensors,
actuators, controllers and a supervisor.
Literature provides several examples of control strategies applied to natural ventilated building. The
research conducted by Schulze and Eicker (2013) shows that in moderate climate good indoor air quality
can be easily maintained through natural ventilation. However, uncontrolled activation often results in too
low indoor temperature. To deal with this problem, the researchers have developed a control strategy
focusing on three objectives. The preservation of indoor air quality, achieved planning 5 minutes openings
at 50% of the effective opening areas when the indoor CO2 level exceed the outdoor one of a certain
concentration. The thermal comfort is ensured including specific algorithms that avoid overcooling during
heating and intermediate seasons. The risk of local thermal discomfort, as air drafts, is avoided modulating
the opening area as function of the difference between indoor and ambient air temperature. Paoletti et al.
(2014) designed an n-ZEB natural ventilated office in Italy. The implemented control aims to establish
optimum interior thermal comfort conditions. It includes activation thresholds related to exterior, interior
and dew point minimum temperature. A relative humidity control is also integrated. Allard (2002) and
Nicol et al. (2007) highlight the importance of planning a dead band, an area within which there is not need
for the opening state to change. The scope is the promotion of the stability of the system. Dell’Osso et al.
(2015) calibrated the natural ventilation system of a designed residential building on a variable set-point.
The set-point is based on the optimal indoor temperature, evaluated according to the adaptive comfort
theory. A similar approach is adopted in this thesis.
The control strategy developed for the specific need of the studied sports halls is now described. The
control of the simulated natural ventilation depends on the occupancy, the internal operative temperature
and the CO2 concentration. During daylight hours, natural ventilation is activated only when the building
is occupied. Natural ventilation activation implies that the openings are opened if the operative
temperature exceeds the upper limit of the selected thermal category (category II, which should be
adopted as reference for the design of new building according to UNE-EN 15251) or if the indoor CO2
concentration is outside the acceptability range. Specifically, the interval of indoor tolerable concentration
is restricted respect to the recommendations of the standard. This configuration is introduced to give
52
stability to the system, avoid frequent ON/OFF cycles and allow the removal of the excess CO2 while
there is continuous emission from the occupants. In fact, in analogy with the explanation reported in
Nicol et al. (2007), model that suggests a particular CO2 concentration at which windows are opened are
unstable, since the window opening can itself cause a drop of CO2 concentration resulting in a window
closure, which will in turn cause a rise CO2 concentration and a window opening and so on. The
operation of the control system is implemented in TRNSYS through type 2 (ON/OFF Differential
Controller). The activation (or deactivation) of the ventilation system depends on its actual state.
The control strategy is schematized in figure 34, representing the set points and the dead band
configurations.
As it possible to see in figure 33, the TRNFLOW simulation requires the definition of another parameter:
the opening factor of the windows. In this study, the opening factor have been adjusted to avoid the risk
of overcooling and air draft. At this scope, the opening are more or less opened depending on the
difference between the interior and exterior temperature during the cold season and on the wind velocity
during the warm season (tab.27). Moreover, during the weekend, when the CO2 production is significant
considering the expected greater occupation, the system is forced to work with an opening factor equal to
1, unless the wind velocity is granter than 6 m/s. Again, this condition is suggested to maintain the
stability of the system, namely to avoid that a substantial flow of air can rapidly reduce the pollutant
concentration causing the closure of the openings. Indeed, it is desirable that the natural ventilation
system works constantly during the period of high occupancy.
Table 27. Control strategy. Opening factor variation
Opening factor Summer
Wind velocity (m/s) Winter
𝑻𝒊𝒏𝒕𝒆𝒓𝒊𝒐𝒓 − 𝑻𝒆𝒙𝒕𝒆𝒓𝒊𝒐𝒓 (°C)
0.2 >15 > 9 0.4 15 – 11.25 9 – 7.5 0.6 11.25 – 7.5 7.5 – 5 0.8 7.5 – 3.75 5 – 4 1 < 3.75 < 4
1 if Occ = max and wind velocity < 6m/s
To verify its effect on overheating risk reduction, night ventilation is also tested. Therefore, in summer,
natural ventilation is activated after that the users leave the sports hall if the exterior air temperature is
lower than the interior air temperature. In general terms, set this conditions, natural ventilation stays on
until the morning hours.
Figure 34. Control strategy. Left: thermal comfort control; right: air quality control. Blue line: openings behavior when the actual state of the natural ventilation system is ON. Green dashed line: openings behavior when the actual state of the
natural ventilation system is OFF
53
8.4 Mechanical ventilation
To compare the performance of the tested natural ventilation strategy to the energy and economical
expenditure due to a more conventional installation, TRNSYS is used to model a simple mechanical
ventilation system.
According to the PAV3 document, the forced air renovation requirements for the specific studied case
account for 13’365 m3/h, namely ACH = 0.98 h-1.
To provide the desired external air supply, the installation of an axial flow fan is simulated through the
TRNSYS Fan Type manager (fig.35). The technical features of the selected fan and the relative characteristic
curve are reported in Annex 3. The fan is coupled with a large opening, as reported in table 28. The
contribution of the infiltration is also taken into account. In this regard, when the fan is turned off the air
mass flow coefficient is set to value Cs = 0.0504 kg/s at 1Pa; the flow coefficient per meter crack length is
set to Cs = 0.00504 kg/s/m at 1Pa.
Table 28. Description of the mechanical ventilation system
Description Dimension
[m2] Maximum air flow
[m3/h] Position: high [m]
North-West façade Fan (airlink 1) - 15’350 6.30 South-East façade Opening-Horizontal sliding (airlink 2) 5 - 0.45
Regarding the operation of the mechanical ventilation system, the effectiveness of three different control
strategies is evaluated:
Figure 35. TRNFLOW mechanical ventilation simulation
54
NO CONTROL (MV): the mechanical ventilation system works at its maximum capacity when
the sports hall is occupied. The opening factor of the opening results always 1, as well as the fan
speed factor, a parameter that, as it possible to see in figure 35, must be defined in TRNFLOW in
case of mechanical ventilation simulation.
CONTROL (MV+CTL): the activation of the mechanical system is regulated by the same control
implemented for the natural ventilation installation. However, the speed of the fan and the
opening factor of the opening is fixed to 1.
VARIABLE (MV+DC): the mechanical ventilation system is activated only when the building is
occupied. The speed of the fan and the opening factor are function of the CO2 concentration
inside the building, correlated to the occupancy level (fig.36). In other words, the performance of
a demand controlled ventilation (DCV) system is simulated (Lawrence 2004). A DCV system
adjusts outside ventilation air based on the number of occupants and the ventilation demands that
those occupants create. The aim is to reduce energy penalty due to over ventilation during period
of low occupancy (Emmerich and Persily, 1997).
The affinity laws of fans allow to calculate the delivered airflow and the relative absorbed power (Vogt
2012) (eq. 19 and eq. 20) in case of variable speed installation.
𝑄1
𝑄2=
𝑁1
𝑁2
𝑃1
𝑃2= (
𝑁1
𝑁2)
3
Where Q is the air flow rate expressed in m3/s, N the fan speed in rpm and P refers to the fan power in
W.
0 100 200 300
0,0
0,2
0,4
0,6
0,8
1,0
op
en
ing
an
d f
an
sp
eed
fac
tors
occupation
Figure 36. Demand controlled ventilation
(eq. 19)
(eq. 20)
55
The heating demand that emerges in case of operation of the mechanical ventilation system is satisfied
through the installation of an electric heaters battery that preheats the external air before it is introduced
into the sports hall by the fan. The type 6 (HVAC\Auxiliary Heaters) is used in TRNSYS to simulate the
electric heater battery behavior (TRNSYS 2010). The maximum heating rate is calculated according to the
equation:
��𝑚𝑎𝑥 = �� ∗ 𝑐𝑝 ∗ ∆𝑇 = 𝑚 ∗ 𝑐𝑝 ∗ (𝑇𝑠𝑒𝑡𝑝𝑜𝑖𝑛𝑡 − 𝑇𝑒𝑥𝑡) (eq. 21)
Where �� [kg/h] is assumed equal to the average net mass flow through the operating fan; 𝑐𝑝 is the
specific heat of the air (1.005 kJ/kgK)); 𝑇𝑒𝑥𝑡 is considered as the minimum exterior temperature registered
along the year (0.2°C); 𝑇𝑠𝑒𝑡𝑝𝑜𝑖𝑛𝑡 is evaluated taking into account the amount of exterior air introduced in
the sports hall. The introduced exterior air is less than the entire indoor air volume, therefore it must be
heated up to a temperature higher than the desired comfort temperature of 14°C. The resultant heating
rate, required to heat up the fluid (exterior air) to a certain 𝑇𝑠𝑒𝑡𝑝𝑜𝑖𝑛𝑡 temperature, is added as an additional
heat gain in the simulation. The scope is to evaluate the impact of a potential heating system on the
thermal behavior of the building, as well as to calculate its energetic and economic costs. Finally, it is
specified that the control of the heating system forces the heaters to work only when the sports hall is
occupied and the exterior temperature goes below a certain limit value (between 8°C and 11°C, depending
on the different operation modes of the mechanical ventilation system).
56
9 PV system design
PV Building Integration (BIPV) is a practice that refers to the use of PV modules as architectural
elements, being a collaborative part of the design of the building envelope and having an architectural
function in symbiosis with functional properties and economic regenerative energy conversion (Achenza
and Desogus, 2013). Part of this research has dealt with the test of different PV system configurations
designed to contribute to the energy needs of the investigated sports facility. The analysis is performed
through the Google Sketchup plug in Skelion (Skelion v5.1.9 2015). The software Skelion allows to insert
solar panels in any surface of the building, previously modelled in Google Sketchup and geolocalized
through Google Hearth. It is possible to modify, within other features, position, azimuth and tilt of the
panels. The software, taking into consideration the shading that solar obstructions project on the panels in
different period of the year, supports the design of the PV system minimizing the shading losses. In the
specific analyzed case study, this feature has been useful, for instance, to consider the effect of the
installation of skylights on the roof and to evaluate the no shaded surface available for the PV modules.
Connected to the simulation software packages PVsyst (PVsyst SA 2012) and PVwatt (Alliance for
Sustainable Energy, LLC, 2016) Skelion is able to evaluate the annual and average monthly electricity
production of the modelled PV systems, its yield as well as its shading losses.
The findings of the Skelion simulation are shown in the corresponding results section 11.3.
Within the 16 tested PV system configurations, 4 have been selected for a further study. The selection has
been made taking into account the economic convenience (case 2 and case 6) or the peculiar
architectonical integration into the studied building (in case 12 the PV panels are integrated into the
building façade, while in case 15 the PV panels are installed on the shading device). The selected
configurations have been simulated in TRNSYS through type 94 (Photovoltaic Array). This additional
analysis has been necessary to evaluate the PV system production on 6 minutes basis. This means, to have
results comparable to the building TRNSYS simulation outputs that include the time steps of functioning
(and consequently of consuming) of the ventilation system (the activation of the fan, for the mechanical
ventilation scenario, or of the engines that turn on the opening, for natural ventilation scenario), of the
heating and of the artificial lighting systems. Also the consumptions indicated as others (considered electric
consumptions) are time-depending: occur only when the building is occupied. The final objective is to
perform, for any time step along the one-year simulation, an energy balance between the electricity
demand and the electricity production. Therefore, overall, it has been possible for the different scenarios
to calculate the self-consumption of site and the amount of exported energy.
It is anticipated that the two used programs return different results. The observed discrepancy is due to
various reasons:
TRNSYS PV array simulation does not account for performance losses. Conversely, Skelion
resulting electricity generation is discounted of system losses, according to default values (tab.29),
as well as of estimated shading losses.
Skelion photovoltaic system performance predictions do not reflect variations between PV
technologies. PV modules with better performance are not differentiated from lesser performing
ones. The program specifies that Shell Solar S115 commercial modules are installed. However, the
only information implemented in the simulation regards the dimension of the module (outside
dimension (mm) = 1220x850), necessary to identify the most convenient array configuration for
the available surface. On the contrary, type 94 requires the introduction of several module
specific parameters. The characteristics of the simulated module (Shell Solar S115) used as
TRNSYS inputs are reported Annex 4.
57
Table 29. Default values for the system loss categories (Dobos 2014)
Category Default Value (%)
Soiling 2
Shading 3
Snow 0
Mismatch 2
Wiring 2
Connections 0.5
Light-Induced Degradation 1.5
Nameplate Rating 1
Age 0
Availability 3
Therefore, taking into account the reported considerations, it has been deemed appropriate elaborate the
TRNSYS outputs, subtracting from the resultant PV generation the losses reported in table 29 as well as
the shading losses calculated by Skelion for each configuration on monthly bases (Annex 5).
58
10 Cost-optimality methodology
In line with the European Union building policies tendency to move toward an integrated approach that
takes into account simultaneously energy, environmental, financial and comfort related aspect, the results
of a cost-optimality analysis are elected as an additional indicator for the comparison of the proposed
sports hall systems configurations (BPIE 2013).
Cost optimal level is the energy performance level which leads to the lower costs during the estimated
building economic lifecycle (Official Journal of the European Union 2012). A set of actions is cost optimal
when maximize the net present value (NPV, calculated according to UNE-EN 15459 (AENOR 2008b))
of cost effective measures, namely measures characterized by benefits higher than the cost of their
implementation over the expected lifetime (BPIE 2013).
The implementation of the cost-optimality methodology provides a useful comparative framework to
study cost optimal and n-ZEB solutions, in terms of costs, primary energy consumption and CO2
emissions savings. The energy performance is measured in kWh/m2 of primary energy. The calculation of
primary energy, performed taking into account the national primary energy conversion factors, includes
the energy consumption due to space heating, cooling, ventilation, domestic hot water and lighting
systems. The total primary energy demand must be discounted of the renewable energy produced on-site
(European Commission 2016c).
Given a specific set of measures, the cost-optimal approach aims to evaluate its global cost. Global cost is
defined as the results of the calculation of the present value of all the costs during a long period, taking
into account the residual values of components with longer lifetimes (fig.37). Conforming to the cost-
optimality procedure, cost calculation must include operational, maintenance, disposal and investments
costs. Energy costs regard consumed energy-related costs and exported energy-related costs.
Environmental costs due to the CO2 emissions are not considered in this study, which adopts a financial
prospective (building owner and investor perspective). On the contrary, taxes (VAT) are included. All the
costs have been introduced in the calculation according to the corresponding evolution rates (tab.30).
Discount rates reflects national financing environment and mortgage conditions.
Table 30. Description of the evolutions rates implemented in the cost-optimal calculations. Source: Ortiz et al. (2016a)
Economic term Evolution rate calculation
Replacement cost Discount rate (RD) 𝑅𝑅 = −
𝑅−𝑅𝐼
1+(𝑅𝐼 100⁄ ) [%] (eq. 22)
Disposal cost Market interest rate (R)
Maintenance cost Inflation rate (RI)
𝑅𝐷 = −1
1+(𝑅𝑅 100⁄ )𝑡 [-] (eq. 23) Additional values for
purchase/sale energy Real interest rate (RR)
Energy cost Energy evolution rate (RE)
𝑅𝐸 = (1 + 𝑅𝑋𝐸 100⁄ )𝑡−1 [-] (eq. 24) Energy cost evolution (RXE)
t, the year of calculation
59
10.1 Calculation hypothesis
As described in the previous section, to perform a cost-optimality evaluation it is fundamental the
availability of energetic, economic and system components data.
Table 31 reports the energy costs hypothesis, while table 32 shows the assumed economic parameters.
Table 31. Energy and environmental hypothesis for the cost-optimality analysis
Parameter Electricity Natural gas
Consumed Exported
Energy cost (€/kWh) (Ortiz et al.,
2016a)
0.1315 0.06575 0.0527
Additional values for purchase (€/y) 178.552 0 106.56
Energy cost evolution, RXE (%) 2.5 2.5 2
Conversion factor from final energy to total
Non-renewable primary energy (kWhp/kWhf) (RITE 2014)
1.954 0 (Musall and
Voss, 2014) 1.190
Conversion factor from final energy to CO2
emissions (gCO2/kWhf) 331 0 252
Figure 37. Global cost calculation. Source: Ortiz et al. (2016a)
60
Table 32. Economic hypothesis for the cost-optimality analysis
Parameter (Ortiz et al. 2016a) %
Inflation Rate (RI) 2
Market interest rate (R) 4.5
VAT 21
Overall, this study evaluates the cost optimality level of 24 scenarios that result from the combination of
the different simulated ventilation modes, control strategies, PV system configurations and heating
systems, chosen, as mentioned in table 20, within energy efficient alternatives as heat pump and
condensing boiler.
In the simulation of the natural ventilation cases, the heating load of the studied sports hall is evaluated
through the TRNSYS Heating Type Manager tool. The heating system is sized to ensure a minimum indoor
temperature of 14°C during the occupation periods. Regarding the case of mechanical ventilation, it is
assumed that the heating requirements are met through the installation of electric heater batteries. The
heating system is sized according to the maximum heating requirements resulting from the calculation
reported in section 8.1. The heating demand is available as a TRNSYS simulation output. To evaluate the
final energy consumption due to heating purpose, TRNSYS results are elaborated taking into account the
efficiency of the heating devices, as well as the efficiency of the emission and distribution systems.
The characteristics of the systems components are reported in table 34. The information regarding the
maintenance costs and the lifetime are consistent with the indication reported in the standard UNE-EN
15459. Systems components costs are extrapolated form a Spanish construction price database (CYPE
Ingenieros, S.A. 2016). The costs of the ventilation equipment come from the Soler y Palau (S&P 2016)
price list. The costs of the devices involved in the implementation of the ventilation control, as wind
speed, CO2 concentration and temperature sensors, are considered negligible.
Some additional assumptions are made:
the replacement cost of the automatic opening accounts only for the replacement of the
mechanical part of the component, assuming that the lifespan of the opening itself is considerably
longer than the engine one;
the control system implemented in case 1 manages only the building ventilation while the one
implemented in case 4 manages only the heating devices. Therefore, their costs are lower respect
to the costs considered for the other analyzed cases.
The sports hall falls in the category of non-residential building. Therefore, its life cycle is considered to be
20 years (Official Journal of the European Union 2012).
The costs of the PV systems are also included in the cost-optimal calculation:
Table 33. PV system costs. Source: Huld et al. (2014)
Investment costs (€/kWp) Replacement costs (€/kWp) Maintenance costs (€/y) Lifespan (y)
1’400 1’400 28 20
61
Table 34. System components costs
Case Systems
components
Investment
costs (€)
Replacement
costs (€)
Maintenance
costs (€/y)
Lifespan
(y) η
1 Natural
ventilation
Automatic
Openings 9 m2
(2x)
5’364 1’259 119 20
Control system 662 662 23 20
2
Natural
ventilation +
heat pump
Automatic
Openings 9 m2
(2x)
5’364 1’259 119 20
Heat pump
(33.5 kW) 17’758 17’758 621 17
4.27
(Ortiz et
al.,
2016b)
Distribution and
emission system
(4x11.4 kW)
6’017 6’017 168 20 0.89
Control system 1’018 1’018 35 20
3
Natural
ventilation +
condensing
boiler
Automatic
Openings 9 m2
(2x)
5’364 1’259 119 20
Condensing
boiler
(50kW)
4’364 4’366 412 20
1.09
(Ortiz et
al.,
2016b)
Radiant panels
(24x6m) 5’286 5’286 89 50
0.89
(Qrad
2016)
Control system 1’018 1’018 35 20
4
Mechanical
ventilation +
no control
Automatic
Opening 5 m2 2’161 564 49 20
Fan 1’145 1’145 108 17
Electric heater
(50 kW) 2’340 2’340 35 17 0.9
Heaters control 355 355 10 20
5
Mechanical
ventilation +
control
Automatic
Opening 5 m2 2’161 564 49 20
Fan 1’145 1’145 108 17
Electric heater
(50 kW) 2’340 2’340 35 17 0.9
Control system 1’018 1’018 35 20
6
Mechanical
ventilation +
variable
speed
Automatic
Opening 5 m2 2’161 564 49 20
Fan 1’145 1’145 108 15
Electric heater
(16.5 kW) 1’094 1’094 16 17 0.9
Speed control 937 937 40 20
Control system 1’018 1’018 35 20
62
11 Results and discussion
The following subchapters present the outcomes of the different sections previously reported. The results
are moreover discussed and an energy balance is performed.
11.1 Measurement campaign
The data collected through the measurement campaign have been elaborated according to the comfort
models described in section 3.2. The objective is to analyze the comfort conditions of the selected sports
hall. Some aspects of the adopted models must be clarified.
The Fanger model, as well as the adaptive approach, have been developed for building environment
significantly different from the case study investigated in this thesis. Similarly, the used standards do not
contain specific indication for sports buildings.
Regarding the critical issues related to the Fanger model, it is highlighted that such approach has been
elaborated for mechanical ventilated spaces and validated mainly for office and residential buildings
(Pagliano et al., 2012; Gilani et al., 2015). Moreover, the PMV theory is based on steady-state parameters,
while usually a sports hall is an environment characterized by non-homogenous users profile and where
transient conditions occur, as the changing of the metabolic rate and the evaporative heat loss (Revel and
Arnesano, 2014b).
In detail, to implement the proposed adaptive methodology, the studied space should comply with
different requirements (Emmerich et al. 2011):
presence of windows that open to the outside
no mechanical cooling system
metabolic activity of the occupants between 1.0 and 1.3 MET
possibility of clothing adaptation for the users
monthly outdoor temperatures below 33.5°C and above 10°C
The users of the Terrassa sports building perform activities characterized by a MET outside the
applicability range (tab.16). Additionally, the players are not completely free of changing their clothes
according to the perceived thermal sensation. Revel and Arnesano (2014a) point out that another
limitation of the adaptive thermal model in case of sports facilities thermal comfort evaluation, is related
to the fact that the model is not able to consider the effect of skin wetness.
11.1.1 Survey results
The comfort surveys have been conducted during the period of data acquisition and have been directed to
the occupants of the monitored area. The completed surveys have been in total 54. However, only 19
answers have been given to the question regarding the air perception
According to the results of the survey (fig.38), 84% of the audience was experiencing a thermal
discomfort, mainly due to overheating: 33% affirmed that the environment was slightly warm, 28% that it
was warm and 17% that it was very warm (only 3 people considered it slightly cold.). Regarding the
humidity, the majority of the audience (65%) considered the environment neutral, while the air movement
was perceived mainly as inadequate (slightly low for 33% and very low for 37%). The lighting was
evaluated neutral by 54% of the audience.
63
very cold (-3)
cold (-2)
slightly cold (-1)
neutral (0)
slightly warm (1)
warm (2)
very warm (3)
0 5 10 15 20 25 30
Thermal sensation
Figure 38. Comfort survey results
very dry
slightly dry
dry
neutral
slightly wet
wet
very wet
0 5 10 15 20 25 30
Humidity
very low
slightly low
low
neutral
sligthly high
high
very high
0 5 10 15 20 25 30
Air movement
very intense
slightly intense
intense
neutral
slightly dim
dim
very dim
0 5 10 15 20 25 30
Lighting
laden
slightly laden
fresh
0 5 10 15 20 25 30
Air perception
64
11.1.2 Thermal comfort analysis
This section reports the results obtained from the comfort evaluation of the “Poliesportiu Pla Del Bon
Aire” of Terrassa. The interior thermal comfort of the sports hall has been assessed using the PMV
Fanger model, the adaptive model, according to the UNE-EN 15251 and ASHRAE 55-2010 standards,
the Givoni diagram and the heat stress methodology previously described (section 3.2).
The air temperature used for the calculation is the one registered at 1.4 meters height.
PMV - Fanger model
Firstly, the thermal sensation evaluated by the audience through the survey is compared to the results of
the PMV calculation (fig.39). The survey answers have been averaged for each considered time period.
Observing figure 39, it is possible to notice that in a few cases the thermal sensation perceived by the
audience does not correspond to the calculated PMV. During the hours of maximum occupation (from
18:30 to 21:30), it occurs that the divergence is more evident. Overall, the survey and the calculation
confirm that generally the PMV index deviates from the condition of neutrality (PMV = 0). Mostly, the
thermal environment results to be slightly warm or warm. It is perceived very warm by some users.
From the analysis of the PVM indices and according to the classification introduced by UNE-EN 15251
(tab.35), the comfort categories that characterize the existing sports hall are determined. (fig.40).
Figure 39. PMV index comparison. Tower 1 and Tower 2 indicate the results of the calculation implemented following the Fanger model
09:36 12:00 14:24 16:48 19:12 21:36
0,0
0,5
1,0
1,5
2,0
2,5
3,0
PM
V
Tower 1 Tower 2 Survey answer
PMV comparison
65
Table 35. Building category according to UNE-EN 15251
Category PPD
%
I <6 -0.2<PMV<+0.2 High level of expectation, recommended for spaces occupied by
people with special requirements
II <10 -0.5<PMV<+0.5 Normal level of expectation; for new and renovated buildings
III <15 -0.7<PMV<+0.7 Acceptable and moderate level of expectation; for existing
buildings
IV >15 PMV<-0.7;or
+0.7<PMV Acceptable only for a limited part of the year
Figure 40 shows clearly that, during almost all the occupied period (more than 90% of the time), the
audience is in condition of thermal discomfort. The situation is slightly better in the case of Tower 1,
located farther from the audience seats and from windows than Tower 2.
The reasons that determine the reported thermal discomfort are investigated analyzing Category IV more
in detail (tab.36).
Table 36. PMV index classification for Category IV
Category IV PMV≤ -0.7 0.7≤PMV<1 PMV≥1
Tower 1 0% 13% 87%
Tower 2 0% 5% 95%
The values reported in table 36 confirm that the thermal discomfort is related to the perception of an
excessive increase of the indoor air temperature.
91
96
Tower 1
Tower 2
--
0 20 40 60 80 100
I II III IV
Comfort categories
%
Figure 40. Thermal comfort classification according to the calculated PMV index
66
Regarding the thermal comfort analysis of the players, the application of the Fanger model results in a
condition of thermal discomfort due to overheating for the entire interval of measurements, as
consequence of players high metabolic activity. For this reason, the players comfort is additionally
assessed through the Required Sweat Rate methodology (section 3.2.3)
Required Sweat Rate
Table 37 reports the UNE-EN ISO 7933 reference values adopted for the evaluation of the thermal stress
conditions of the players in the sports hall.
Table 37. UNE-EN ISO 7933 reference values for thermal stress and strain evaluation
NON
ACCLIMATISED ACCLIMATISED DLE
Criteria for
MET≥65W/m2
Warning
Danger Warning Danger
DLE1 = 60 Qmax / (Ereq -Ep)
DLE2 = 60 Dmax / SWp
where
Ep - predicted evaporating rate
SWp - predicted sweat rate
The shortest DLE shall be used for limiting
the duration of work.
Wmax 0.85 0.85 1 1
Qmax (Wh/m2) 50 60 50 60
Dmax (Wh/m2) 1’000 1’250 1’500 2’000
SWmax (W/m2) 200 250 300 400
The DLE sets the acceptable work period advisable to avoid dehydration, excessive heat storage and skin
wettedness. The DLE values calculated according the UNE-EN ISO 7933 procedure and determined for
the warning and danger categories, are summarized in table 38.
Table 38. Duration Limited Exposure
DLE (minutes)
NON ACCLIMATISED ACCLIMATISED
Warning Danger Warning Danger
28.87 41.58 74.41 219.00
Considering the duration of an average basket match (4 periods of 10 minutes each), the thermal
environment results appropriate for players activity.
67
Adaptive comfort model
As anticipated, the sports hall indoor thermal comfort is investigated according to the thermal adaptive
model. The standards ASHRAE 55-2010 and UNE-EN 15251 are applied.
The UNE-EN 15251 approach (section 3.2.2) is based on the average exponential daily temperature. In
this report only the results related to day 13/03 are presented (tab.39, fig.41).
Table 39. Thermal comfort categories. Adaptive model UNE-EN 15251
Category MAX operative temperature (°C) MIN operative temperature (°C)
I 23.72 19.72 II 24.72 18.72 III 25.72 17.72
The indoor operative temperature, for Tower 1 and Tower 2, remains into the range of Category I for most
of the occupied period. However, between 13:30 and 18:00, when the interior air temperature reaches its
maximum (fig.23), the operative temperature curve lies in Category II and even in Category III.
Following the ASHRAE 55-2010 standard, the resultant comfort acceptability ranges, calculated referring
to the average monthly exterior temperature (section 3.2.2), are (tab.40):
Table 40. Thermal comfort categories. Adaptive model ASHRAE 55-2010
Acceptability MAX operative temperature (°C) MIN operative temperature (°C)
90% 26.59 28.59
80% 16.59 14.59
Figure 41. Indoor operative temperature and comfort categories according to the UNE-EN 15251 standard
09:36 12:00 14:24 16:48 19:12 21:36
12
16
20
24
28
Op
era
tiv
e t
em
pe
ratu
re (
°C)
Operative Temperature Cat.I MAX Cat.I MIN
Cat.II MAX Cat.II MIN Cat. III MAX Cat.III MIN
Adaptive model UNE-EN 15251 Tower 1
09:36 12:00 14:24 16:48 19:12 21:36
12
16
20
24
28
Op
era
tiv
e t
em
pe
ratu
re (
°C)
Operative Temperature Cat.I MAX Cat.I MIN
Cat.II MAX Cat.II MIN Cat. III MAX Cat.III MIN
Adaptive model UNE-EN 15251 Tower 2
68
The operative temperature registered in the sports hall is inside 90% acceptability range for the entire
occupied period (fig.42).
Taking into account the considerations reported at the beginning of this section (section 11.1), figure 41
and figure 42 show that the comfort parameters registered in the sports hall are inside the acceptability
ranges defined by the ASHRAE 55-2010 and UNE-EN 15251 standards.
Givoni diagram
The Givoni diagram (fig.43) reports the interior and exterior information about temperature and relative
humdity in a psychometric chart. The represented data corresponds to the measurements carried out
during the occupation hours (09:30 - 21:30). The diagram is divided in five areas, depending on the action
required to ensure indoor thermal comfort:
heating zone (blue)
cooling and dehumidification zone (red)
cooling and humidifying zone(yellow)
comfort zone (green)
comfort zone with natural ventilationand air velocity of 1m/s (green dottet line)
Figure 43 shows that almost all the measurements realized during the occupation period comply with the
comfort requirements.
As mentioned before, the studied sports facility is not equipped with a mechanical ventilation system,
therefore the comfort zone referred to natural ventilated building should be considered. However, as
reported in figure 25, the indoor air velocity values recorded during the measurement campaign are lower
than the reference value of 1 m/s.
Figure 42. Indoor operative temperature and comfort categories according to the ASHRAE 55-2010 standard
09:36 12:00 14:24 16:48 19:12 21:36
12
16
20
24
28
Op
era
tive t
em
pera
ture
(°C
)
90% max 90% min 80% max 80% min
Operative temperature
Adaptive model ASHRAE 55-2010 Tower 1
09:36 12:00 14:24 16:48 19:12 21:36
12
16
20
24
28
Op
era
tiv
e t
em
pe
ratu
re (
°C)
90% max 90% min 80% max 80% min
Operative temperature
Adaptive model ASHRAE 55-2010 Tower 2
69
Figure 43. Givoni diagram. Source: self-elaboration based on Al-Azri et al. (2012)
Relative Humidity
UNE-EN 15251 standard establishes relative humidity comfort criteria for building characterized by
human occupation (tab.41).
Table 41. Relative humidity categories according to the UNE-EN 15251 standard
Category Maximum % Minimum %
I 50 30 II 60 25 III 70 20 IV >70 <20
The sports hall relative humidity falls in Category I for most of the investigated time (fig.44). Relative
humidity percentage reaches Category II during the night and in condition of maximum occupation. The
values registered by Tower 2 lays also in Category III. It is evident the relationship occurring between the
occupation level and the indoor relative humidity. Relative humidity, in fact, decreases significantly during
the break (14:00) and then increases sharply again following the increment of the sports hall occupation.
70
11.1.3 Air quality: indoor CO2 concentration
Through the elaboration of the field measurements results, it is possible have information regarding the air
quality inside the studied sports facility. The air quality categories are identified according to the UNE-
EN 15251 standard requirements and taking into account the exterior CO2 concentration (450 ppm)
(tab.42).
Table 42. CO2 concentration categories according to the UNE-EN 15251 standard
Category Allowed CO2 concentration (ppm) above the exterior value
I 350 II 500 III 800 IV >800
Figure 44. Relative humidity comfort categories. Left: relative humidity registered along the two days of measurements. Right: relative humidity and sports hall occupation
Figure 45. CO2 concentration measurements and comfort categories
001:00:00 002:04:48 002:09:36 002:14:24 002:19:12
20
30
40
50
60
Re
lati
ve
Hu
mid
ity
(%
)
HR tower 1 HR tower 2
Cat.I max Cat.I min Cat.II max Cat.II min
09:36 12:00 14:24 16:48 19:12
20
30
40
50
60
occupation
Re
lati
ve
Hu
mid
ity
(%
)
50
100
150
200
250
300
350
09:36 12:00 14:24 16:48 19:12 21:36
400
600
800
1000
1200
1400
1600
1800
2000
2200
sensor 1 Cat.I Cat.II Cat.III tower 2 occupation
CO
2 (
pp
m)
0
100
200
300
71
It can be observed that the quality of the air inside the sports hall is good during the night (fig.26), worsen
rapidly when the building starts to be occupied and is very poor in condition of maximum occupation
(fig.45). In analogy with the presented relative humidity behaviour (fig.44), CO2 indoor concentration
increases significantly during the evening. It results that the comfort condition recommended by the
UNE-EN 15251 standard are not met starting from 19:00 until the end of the measurements period, when
the CO2 concentration value reaches Category IV.
The main findings of the measurements campaign are briefly summarized.
Taking into account that the adopted standards are not specifically elaborated for sports facilities
and for the consequent high level of metabolic activity of the users (the reasons of the inadequacy
are explained in detail at the beginning of this section), the results of the thermal comfort analysis
show that the adaptive comfort requirements (indoor operative temperature ranges) reported in
the ASHRAE 55-2010 and in the UNE-EN 15251 standards are mostly complied.
The relative humidity, according to the standard UNE-EN 15251, is acceptable.
The thermal stress is acceptable as well.
Conversely, looking at the level reached by the interior CO2 concentration and following the
recommendation proposed by the UNE-EN 15251, it has been verified that the users of the
sports hall experience periods of discomfort due to poor air quality (when the occupation is
maximum).
The results of the survey regarding the audience thermal sensation and the calculated comfort
parameters don’t coincide. A possible reason could be that the comfort index does not evaluate
the relative humidity and the CO2 concentration. The excessive CO2 concentration during the
hours of maximum occupation and, to a certain extent, the simultaneous sharp increase of the
indoor relative humidity appear as the possible main causes of the perceived discomfort emerged
through the survey.
72
11.2 Ventilation strategies
The objective of the building simulation is to verify to which extend the selected n-ZEB strategies are able
to reduce the primary energy consumption of a typical sports hall without causing discomfort to the users.
11.2.1 Natural ventilation results
Observing figure 46, showing the TRNSYS simulation outputs for selected summer and winter control
weeks, it results that the designed control system works correctly. Figure 46 shows, in fact, that the
openings are opened when the CO2 concentration increase excessively during period of sports hall
occupation. However, it occurs that during the weekend, when the occupation is maximum, if there is not
enough exterior wind, the CO2 concentration exceeds the limits set to 1200 ppm (as it is possible to notice
in figure 46, July week case, blue circle). On the other hand, the thermal comfort requirements are fulfilled
most of the simulation time. However, the indoor temperature is close to the lower temperature limit of
14°C when, during the weekend, the openings are completely opened for air quality reason but the
exterior temperature is significantly low (as it is possible to notice in figure 46, February week case, green
circle).
001:18:00 003:12:00 005:06:00 007:00:000
4
8
12
16
20
24
28
32
Operative Temperature on/off T_exterior Top_MAX
T_min Top_MIN Wind velocity Q*100 CO2_MAX CO2
Te
mp
era
ture
(°C
)
0800
1600
2400
3200
Q*1
00 (
m3/s
); C
O2 (
pp
m)
July
001:18:00 003:12:00 005:06:00 007:00:000
4
8
12
16
20
24
28
32
Operative Temperature on/off T_exterior Wind velocity
Top_MAX T_min Top_MIN Q*100 CO2_MAX CO2
Te
mp
era
ture
(°C
)
February
0800
1600
2400
3200
Q*1
00
(m
3/s
); C
O2 (
pp
m)
Figure 46. System behavior during selected winter and summer control weeks
73
The maximum registered ACH is 9.97 h-1. The average ACH with natural ventilation ON is 1.57 h-1, while
the infiltration on average equals to 0.05 h-1. The presented results are achieved without the introduction
natural night ventilation.
The following figure (fig.47) presents more in detail the airflow behavior (FLNEL, net mass flow through the
opening). According to the control strategy, the openings are activated when the indoor CO2 concentration
increases as much as it reaches values above the comfort limit. Therefore, external air can enter into the
building. Positive air flow corresponds to air movement from From-Node to To-Node (section 8.3)
according to the TRNLOW convention. For the studied case, it results that when the airflow is positive,
the external air enters from the North-West opening, goes through the sports hall and exits from the
opening located in the South-East façade. Conversely, when the air flow results negative, the airflow
follows the opposite pathway, namely it enters from the South-East façade and exits from the opening
located in the North-West façade. TRNFLOW takes into account the contribution of the two physical
principles that govern natural ventilation (section 3.1.1), the wind pressure acting on the building façade
(defined as the difference between the local pressure on the surface and the static pressure of the
undisturbed wind at the same height) and the buoyancy resulting from temperature and air composition
differences. In the graphs (fig.46 and fig.47), it is not easy to distinguish the effect of each driving force,
considering that generally they occur at the same time. However, typically thermal buoyancy dominates
during cold periods with almost no wind. During those time steps, air displacement involves the cold and
dense air entering from the bottom opening and the buoyant air leaving from the one installed at the top
of the sports hall façade. During windy days, it is the wind direction that determines the airflow direction.
Figure 47. Air flow in the natural ventilated sports hall. FLNEL: net mass flow per link, TRNFLOW output. FLNEL_NW: net mass flow through North-West opening; FLNEL_SE: net mass flow through South-East opening
001:18:00 003:12:00 005:06:00 007:00:00
-400
00
-200
00
0
2000
0
4000
0
Air
flo
w (
kg
/h)
wind velocity FLNEL_NW = FLNEL_SE
February
0
5
10
(m/s
)
001:18:00 003:12:00 005:06:00 007:00:00
-400
00
-200
00
0
2000
0
4000
0
Air
flo
w (
kg
/h)
wind velocity FLNEL_NW = FLNEL_SE
July
0
5
10
(m/s
)
74
Different criteria have been used to evaluate the achieved comfort conditions:
yearly exceedance: on yearly base, the number of time steps during which the considered
parameters are outside the set comfort ranges;
hours of daily exceedance: the maximum number of discomfort hours registered during one day;
degree of exceedance: to which extent the limits are exceeded.
Thermal discomfort and air quality condition are assessed only during the occupied hours. It is assumed
that the overheating phenomenon occurs if 𝑇𝑜𝑝𝑖𝑛𝑡 > 𝑇𝑜𝑝𝑜𝑝𝑡 + 3, as the technical indications provided by
the Catalan sports council do not set a maximum indoor temperature requirement. The building is
overcooled if the condition 𝑇𝑎𝑖𝑟𝑖𝑛𝑡 < 14°𝐶 is verified.
The TRNSYS results relevant for the comfort evaluation of the building are organized in table 43 and
reported in function of the natural ventilation state, being the only variable parameter.
Table 43. Natural ventilated building: discomfort results
% of the occupied time
winter summer Natural ventilation ON 54.76 50.09 Overcooling 1.69 - Overheating - 0.36 CO2 > 1200 ppm 1.20 0.71
Discomfort occurs mainly during winter. As expected, the excess of CO2 concentration is more significant
during this season, considering that the opening factor has been defined as a trade-off between air quality
needs and the reduction of cold airflow from the outside.
Closely analyzing the discomfort events, it results that for 2 days overcooling occurs during 2.75 hours
that is the maximum consecutive period of overcooling thermal discomfort. The maximum consecutive
period of discomfort due to excessive CO2 concentration is 3 hours and it occurs one day along the
annual simulation. Overall, considering thermal and air quality parameters, good indoor conditions are
ensured for most of the occupied time along the yearly simulation. It is expected that annually the users of
the natural ventilated sports hall would experience only 16 days of discomfort with the distribution shown
in figure 48. The results deviates from the limit values for maximum 329 ppm, 4.61°C in case of
overcooling and 0.48°C in case of overheating (tab.44).
75
Table 44. Natural ventilation. Deviation from the comfort limit values
MAX MIN Average
Overcooling -4.61 °C -0.0025 °C -0.53 °C
Overheating 0.48 °C 0.0005 °C 0.08 °C
CO2 > 1200 ppm 328.96 ppm 0.28 ppm 86.73 ppm
The additional night ventilation further reduces the overheating phenomenon to 0.1% of the occupied
summer time. Therefore, the implementation of night ventilation technique results to have a limited
impact on thermal comfort improvements of this study case building situated in a moderate climate.
However, it is expected that night cooling would be considerably beneficial in extreme climate conditions
and even in moderate climate if phenomenon as heat wave occurs.
0.25 0.5 2.25 6.250
1
2
3
4
5
6
7
fre
qu
en
cy
daily discomfort hours
Overheating
0.25 0.5 1 2 2.5 2.75 6.250
1
2
3
4
5
6
7fr
eq
ue
nc
y
daily discomfort hours
Discomfort
0.25 0.5 0.75 1 1.25 1.5 2 2.5 30
1
2
3
4
5
6
7
fre
qu
en
cy
daily discomfort hours
CO2 concentration
days
days
days
days
Figure 48. Discomfort hours. X-axis=discomfort hours; Y-axis=number of days
76
11.2.2 Mechanical ventilation results
The mechanical ventilation systems, differing for the implemented control strategy, have been simulated
in combination to HVAC\Auxiliary Heaters, as explained in section 8.4. Therefore, for these cases
overcooling events are completely avoided. Regarding the indoor CO2 concentration, although the fan has
been sized according to the indication reported in the PAV3 document, air quality discomfort occur,
except when the fan works without a control strategy. Overheating occurs as well. (tab.45)
Table 45. Mechanical ventilation. Discomfort results
MV MV+CTL MV+DC
% of the occupied period
Ventilation ON winter 100 71.95 100
summer 100 69.80 100
Overheating winter - - -
summer 0.19 0.51 1.01
CO2 > 1200 ppm winter - 0.94 1.15
summer - 1.05 1.48
It results that overheating phenomenon, as in the natural ventilated case, rarely occurs during the year.
However, it slightly increase in case of mechanical ventilated building respect to the natural ventilated one.
At this regards, it is specified that in case of simulation of mechanical ventilation system with variable
speed fan (MV+DC), the summer indoor temperature deviates from the upper limit on average of 0.57°C,
reaching a maximum of 2.02°C.
11.2.3 Energy consumption comparison
The next graph (fig.49) aims to briefly compare the different operations mode of the tested ventilation
mechanisms and control principles. At this scope, the correspondent electric consumptions (including
lighting and ventilation electric needs), are represented for a typical summer day. It results that the daylight
availability strongly influence the energy needs of the simulated building. It is evident that at 20:00 artificial
light system is switched ON, according to daylight availability reported in figure 32. Moreover, the
potential energy savings achievable through the implementation of the natural ventilation strategy clearly
emerges. Implementing natural ventilation, during a typical summer day, it is possible to reduce the
electricity consumption of 21% respect to a mechanical ventilation system without a control strategy. The
energy savings correspond to 17% electricity needs reduction respect to the MV+CTL case and 5%
respect to MV+DC scenario, according with the control strategies explained in chapter 8.3.
77
001:15:12 001:16:36 001:18:00 001:19:24 001:20:48
0,00
0,25
0,50
0,75
1,00
Ele
ctr
icit
y c
on
su
mp
tio
n (
kW
h)
NV MV MV+CTL MV+DC
Weekday July
16:12 17:36 19:00 20:24 21:48
Figure 49. Energy consumption of occupied period in a summer weekday
78
11.3 PV system configurations
Table 46 summarizes the results of the PV designs analysis. As mentioned (section 10.1), the economic
data are extrapolated from Hulb el al. (2014). The comparison of the different PV system configurations
suggests that, considering the available surface for PV modules integration and the weather condition of
the site, the most advantageous solution is the one tested in case 10. In a range of acceptability of 5%
specific cost difference, case 2 and case 6 have similar performance. The mentioned cases are
characterized by the installation of the panels with a slope of 38° and an orientation toward South
direction (182°). The integration of the PV panels in the façade and on the shading device of the building
results less convenient.
Table 46. Tested PV system configurations
Azimuth Slope Panels kWp
Specific
generation
(kWh/kWp)
Total
generation
(kWh)
Specific
cost
(€/kWh)
1
135 20 367 42 1255 52385 1.11
2
182 38 190 22 1364 29807 1.02
3
135 38 568 365 1267 82746 1.10
4
135 37 162 19 1266 23589 1.10
5
135 14 719 83 1230 101718 1.13
6
182 38 302 35 1371 47623 1.02
7
135
17
23
37
441 51
1245
1256
1265
63583 1.11
8
135 37 600 69
1263
1256
1254
1268
1213
86494 1.11
9
135 34 470 54 1269
1258 68374 1.10
10
182 38 294 34 1381 46680 1.01
79
11
225 38 60 7 1297 8352 1.15
12
135 90 68 12 876 10606 1.59
13
135 90 56 10 876 8734 1.59
14
180 0 51 6 975 5718 1.43
15
180 0 70 8 979 7882 1.42
16
180
225
134.66
0
37.6
0
265 35
979
1297
876
37442 1.29
11.4 Energy balance of n-ZEB strategy
As introduced in section 9, within the PV configurations proposed in table 46, case 2, 6, 12 and 15 have
been selected and analyzed in TRNSYS through type 94. For those cases, it has been possible to calculate
the covering factor of the PV electricity production respect to the total electricity consumption of the
natural ventilated sports building. The results referring to the natural ventilated sports building not
equipped with a heating system (case 1 of table 34) are shown in table 47. The total electricity
consumption is 32’297 kWh/yr. The lighting consumption accounts for 13’968 kWh/yr. The electricity
demand due to the automation of the natural ventilation systems is estimated at 509 kWh/yr. Other
electricity consumption have been assumed 12 kWh/m2 (ICAEN 2012), resulting in 17’820 kWh/yr.
Table 47. n-ZEB energy balance. Terminology according to Sartori et al. (2012)
Electricity (kWh/yr) PV 2 PV 6 PV 12 PV 15
Total load 32’297
Total generation 35’425 56’639 8’514 9’492
Total delivered (by the grid) 25’072 23’803 29’759 29’224
Self-consumption 7’224 8’494 2’538 3’073
Total exportation 28’201 48’145 5’976 6’419
Covering factor 22.3 % 26.3% 7.8% 9.5%
As listed in table 20, the installation of a renewable energy system forms part of the package of measures
implemented to realize the design of a low energy sports hall. Specifically, the optimal roof slope and PV
panels orientation have been studied to maximize the energy production. Overall, considering the
80
instantaneous balance between electricity demand and supply along one year of operation of the simulated
sports building, the configuration 6 reported in table 46 results the most advantageous one. Characterized
by the higher value of self-consumption (8’494 kWh/y), PV 6 potentially can give the higher contribution
to the final objective of energy costs and CO2 emissions reduction.
Moreover, it results that the thermal load necessary to comply with the minimum temperature
requirements of 14°C is very low: it equals to 213 kWh/yr, namely 0.14 kWh/m2.
Elaborating the data made available by ICAEN (2012), the obtained results are compared to the heating,
lighting and ventilation performance of a standard triple sports hall and of an efficient one, concerning
which energy efficacy measured are applied. The respective non renewable primary energy requirements
are compared as well. The considered non renewable primary energy conversion factors are reported in
table 31. It is assumed that the PV 6 configuration is installed and that the thermal demand of the
simulated sports hall is covered by the installation of a condensing boiler (η=1.09 according to Ortiz et al.
(2016b)) combined with an emission and distribution system consisting of radiant panels (η=0.9) (case 3
of table 34). The resultant consumption is 217 kWh/yr, generated using natural gas.
From figure 50, it is evident that the selected n-ZEB strategies substantially contribute to the objective of
primary energy consumption reduction.
11.5 Cost-optimal evaluation
Figure 51 and figure 52 present the findings of the cost-optimal analysis performed for 24 different
scenarios, resulting from the combination of each tested ventilation strategy with a different heating
system and PV configuration (section 10.1).
In figure 51, the global costs calculated through the cost-optimal methodology have been organized in a
bar graph that reports as well for each solution the distribution of energy, investment, and maintenance
costs (calculated according to the data reported in table 34). The main results are described.
Figure 50. Left: final energy; right: not renewable primary energy. The data elaborated in the figures include heating, lighting and ventilation needs (other electricity consumption
assumed equals to 12 kWh/m2, are not represented)
81
As expected, the natural ventilation case (NV) combined with the PV configuration 6 (PV6) is the one
characterized by the lower global costs over 20 years. The global cost for this solution is estimated in
60.78 €/m2 (taking into account that the total surface of the simulated sports building is 1’485 m2).
Specifically, energy costs result considerably low (only 3.3% of the global costs). The non renewable
primary energy accounts for 31 kWh/yrm2. The PV covering factor, as reported in table 47, is 26.3%. A
significant energy costs reduction is verified every time that the natural ventilation strategy is combined
with PV 6, the configuration that maximize the electricity self-consumption (tab.47).
All the others scenarios include the evaluation of the contribution of a heating system, installed to cover
the discomfort periods due to overcooling. The demand controlled mechanical ventilation system
(MV+DC) combined with PV6 results the cost-effective solution. PV6 is able to cover 25.3% of the
system electricity consumptions. The non renewable primary energy accounts for 34 kWh/yrm2. The
required global costs are 66.91 €/m2. Energy costs account for 9.76% of the total. DCV investments costs
results slightly lower than the ones for controlled mechanical ventilation system (MV+CTL). DCV
systems are characterized by the fact that allow to modulate the amount of air flow entering into the
ventilated space. As consequence, on one hand, investments costs are reduced because overcooling
discomfort can be completely avoided mounting an electric heaters battery dimensioned for lower thermal
load (16.5 kW instead of 50 kW). On the other hand, an extra expense for the additional fan speed control
it must be taken into account.
The energy costs related to the case of natural ventilation system combined with a condensing boiler
(NV+CB) are lower than in case of MV+DC, resulting 4.9% of the global costs (PV6 case; global costs
are 75.60 €/m2; covering factor of PV6 is 26.3%; non renewable primary energy accounts for 31
kWh/yrm2). However, this solution requires higher investments and maintenance costs. Similarly, the case
of a natural ventilation system coupled with a heat pump (NV+HP) and an electricity generation system
as in PV6 case is characterized by low energy costs. The covering factor of PV6 is 26.25%. Non renewable
primary energy accounts for 31 kWh/yrm2. The installation of the high efficient heat pump ensures good
energy performance of the system: the energy costs accounts only for 2.29% of the global costs (global
costs result 93.04 €/m2), the minimum value within the tested scenarios. However, again the high costs of
the heating device and the reduced electricity demand of the building comport that energy savings do not
balance the economic investments. Overall, the global costs of this solution results greater than for other
scenarios.
Applying to the mechanical ventilation system (MV+CTL) the same control strategy implemented for the
natural ventilation one, it results that the global costs are 74.18 €/m2 (PV6, covering factor 23.58%). This
value is very close to the one calculated for the condensing boiler case (PV6) of 75.60 €/m2. However,
there is a substantial difference in terms of energy costs contribution. For the considered mechanical
ventilation system they account for 18% of the global costs. Non renewable primary energy accounts for
39 kWh/yrm2.
It evident that the installation of a mechanical ventilation system that works at its maximum capacity
during all the occupied period (MV) is the most expensive solution. The reduction of the investments and
maintenance costs (resulting of 2.1% respect to the DCV and the MC+CTL cases combined to PV6) is
significantly lower than the related increase of the energy costs. They account for 51.25% of the global
costs in case of PV6 (global costs result 122.13 €/m2). Specifically, energy costs are 92’966 €, more ten
times higher than in case of mechanical ventilation with variable speed fan and five times more than the
controlled mechanical ventilation case. PV6 is able to cover 14.66% of the system electricity
consumptions. Non renewable primary energy accounts for 73 kWh/yrm2.
Summarizing, the cases characterized by the lowest energy costs involve the installation of natural
ventilation systems. The installation of the heat pump costs in terms of energy almost as much as the
configuration that does not include a heating system. However, it is the most expensive solution at
82
investments and maintenance costs level. Also the condensing boiler solution presents high maintenance
costs. Therefore, to cover the heating needs of the simulated sports halls, the controlled mechanical
ventilation systems result the most convenient ones.
The covering factors of the different evaluated PV system configuration are reported in table 48 for the
different studied cases.
As mentioned (section 10), this work adopts a financial perspective, therefore the CO2 related cost have
not been included in the cost-optimal evaluation. However, in figure 51 the estimated annual CO2
emissions are also reported.
Table 48. Covering factors of the different evaluated PV system configurations
NV NV+HP NV+CB MV+CTL MV MV+DC
PV2 22.37% 22.33% 22.37% 19.83% 12.13% 21.38%
PV6 26.30% 26.25% 26.30% 23.58% 14.66% 25.30%
PV12 7.85% 7.84% 7.85% 7.39% 3.87% 7.30%
PV15 9.51% 9.49% 9.51% 8.04% 4.69% 8.85%
2 6 12 15 2 6 12 15 2 6 12 15 2 6 12 15 2 6 12 15 2 6 12 150
5000
0
1000
00
1500
00
2000
00
2500
00
Co
sts
(€
)
Global costs Energy costs
Investment costs Maintenance costs
5000
1000
0
1500
0
2000
0
CO2 emissions
CO
2 (
kg
/y)
NV+HP
NV+HP
NV+HP
NV+HP
NV+HP
NV+HP
NV+HP
NV+HP
NV
NV
NV
NV
NV
NV
NV
NV
NV+CB
NV+CB
NV+CB
NV+CB
NV+CB
NV+CB
NV+CB
NV+CB
MV+CTL
MV+CTL
MV+CTL
MV+CTL
MV+CTL
MV+CTL
MV+CTL
MV+CTL
MV
MV
MV
MV
MV
MV
MV
MV
MV+DC
MV+DC
MV+DC
MV+DC
MV+DC
MV+DC
MV+DC
MV+DC
Figure 51. Cost-optimal analysis results. Orange line: lowest global costs level including heating system. Green line: lowest global cost level without heating system
83
Figure 52 shows the cost-optimality results in terms of annual not renewable primary energy consumption
(including lighting, heating, ventilation and other electrical needs) and global costs over 20 years. The
results are grouped according to the implemented ventilation and heating strategies. It is easy to notice
that the only configurations that require the consumption of more non renewable primary energy than the
efficient PAV3 proposed by ICAEN (2012), used as reference case, regard the installation of mechanical
ventilation without control. Similarly, it is easy to realize that all the tested solutions are significantly below
the level of non renewable primary energy consumption of a standard PAV 3. The 8 points close to the
graph origin in the left corner, refers to PV system configurations 2 and 6. Again, it is confirmed that
natural ventilation implementation is associate to a significant reduction of primary energy load: not
renewable primary energy consumed in the three natural ventilation scenarios results about 7-8% lower
than in the cost-optimal case (mechanical ventilation with variable speed fan combined with PV6).
However, the costs associated to condensing boiler and heat pump installation negatively influences global
costs.
The presented cost-optimality analysis must be completed with some consideration.
Firstly, the simulation of the mechanical ventilation system and the evaluation of its
correspondent costs have been extremely simplified, being this work more focused on the study
of the role of natural ventilation as passive design strategy. Therefore, elements that usually forms
part of a mechanical ventilation system, as ducts, with an impact on system performance as well
as on system costs, have been neglected.
Moreover, it must be taken into account that a further reduction of the investments costs due to
natural ventilation is possible taking advantage of the combination of the ventilation system with
other architectural elements, usually introduced into the design of the sports building for different
purposes. The use of the openings required to comply with the fire regulation is one of the
examples reported in literature (Flourentzou et al., 2015);
25 50 75 100 125 150 175
50
75
100
125
150
175
Non Renewable Primary Energy (kWh/m2yr)
Glo
bal
co
sts
(€/m
2)
Standard PAV3Efficient PAV3
Figure 52. Cost-energy evaluation: not renewable primary energy consumption vs. global cost over 20 years. Color map: green: natural ventilation without heating system; light blue: natural ventilation with
condensing boiler; blue: natural ventilation with heat pump; orange: mechanical ventilation with control; pink: mechanical ventilation with variable speed fan; dark red: mechanical ventilation without control.
Light-blue circle: PV2 an PV6 configurations
84
According to Ortiz el al. (2016b), currently investments costs results 10-30% lower than the ones
reported in the used price database. Therefore, a certain degree of uncertainty affects the
economic analysis.
From the cost-optimal analysis, it emerges that the introduction of a heating system has an
economic impact on global costs that is greater when heat pump or condensing boiler are
installed. Heat pump and condensing boiler, in fact, are more complex and expensive systems
than simple electric heaters. However, taking into account the other zones that typically form part
of a sports hall, the choice of a natural ventilation configuration that include a heating system able
to cover simultaneously the heating and DHW needs of the lockers rooms (therefore a
configuration that includes the installation of a heat pump or a condensing boiler) appears
beneficial in terms of costs reduction.
85
Conclusion
Under a holistic approach, different energy measures for the design a nearly zero energy Sports Hall have
been tested. A novel aspect of the study is its focus on the peculiarity of the Mediterranean climate
context.
The first step of the research has involved a field measurement campaign in an existing facility. The
obtained data suggest that in a standard sports hall comfort issues are closely linked to indoor air quality
conditions. Excess of CO2 concentration causes discomfort perception, even though the registered
thermal parameters fall within the acceptability range. Secondly, TRNSYS simulation confirms that the
combination of reduction of thermal transmittance of the envelope, optimization of the window surface,
correct façades orientations, introduction of shading devices, installation of energy efficiency systems, and
use of natural and night ventilation, is advantageous for the reduction of heating, cooling and artificial
lighting demand, as well as building global costs. It is verified as well that PV system integration positively
affects the sports hall performance toward n-ZEB standards. Overall, the simulated sports building is
characterized by an energy demand of 22 kWh/m2yr (assuming the installation of a condensing boiler and
considering 12 kWh/m2 of other electrical consumption (ICAEN 2012)), 76% less than a standard sports
hall and 46% less than an efficient one. Considering the contribution of the electricity generation on-site,
the annual total primary energy consumption is estimated in 44 kWh/m2.
Moreover, the described strategies minimize the discomfort period due to overcooling and overheating,
and provide good air quality conditions for most of the occupied time along one-year simulation. The
design of the natural ventilation system and of the relative control strategy plays a relevant role in the
energy performance improvements of the building. It is estimated that the natural ventilated sports hall,
not equipped with a heating system, will be overcooled for 1.69% of the winter occupied time, while CO2
concentration will exceed normative limits only during 0.95% of the year. As said, in this regard it must be
taken into account that all the calculations are based on comfort and thermal standards not elaborated
specifically for natural ventilated and sports building categories.
It is evident that a successful application of natural ventilation strategies requires to overcome several
barriers. In cold or tropical climates, it is necessary to combine ventilation systems respectively to heating
and cooling system. In moderate climates, using the Cook’s (2014) definition, the wide adoption of natural
ventilation principles is linked to the respect of the so-called 3C: control, client understanding and
commissioning. The first parameter has been largely discussed in this thesis and a proper strategy has been
identified to ensure sufficient ventilation for good IAQ without unnecessary heating energy costs during
the cold season and without cooling load during the summer. As regard the client-understanding obstacle,
it is true that the users of a natural ventilated building can be concerned about the exterior environment,
in relation to safety issues, noise level and outdoor air pollution. Moreover, fire and acoustic regulation
can be restrictive regarding the free flow of air inside the building. Commissioning: designers are usually
reluctant to accept the risks related to a certain degree of indoor conditions fluctuation implied in the use
of natural ventilation (Allard 2012). While energy efficient consultants are discouraged by the fact that low
fees are expected to support a more complex design analysis. Moreover, there are few standards
supporting the planners in the openings design process and there is a lack of experience within the
architects, engineering and consultants regarding natural ventilation implementation (Schulze and Eicker,
2013). According to Florentzous’ (ESTIA) words: “There is a need of accounting the energy savings in the national
energy regulations. It is the only way to make this technique able to penetrate the market, because there is nothing to sell other
than engineering fees”.
Finally, it is suggested that future development of the presented study can involve the evaluation of the
sports hall DHW needs and the investigation of the potential contribution of a thermal solar system.
86
Publication
Accili A, Ortiz J., Salom J., Energy strategies to nZEB sports hall, Conference Proceedings EuroSun 2016
Palma de Mallorca (Spain), 11 – 14 October 2016
87
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Annex 1
COMFORT SURVEY This survey is part of a research project regarding thermal comfort in Sport Halls, performed by the Catalan Institute of Energy Research with the collaboration of the Club Natació Terrassa. Please, answer the survey half an hour after reaching your sit.
Thank you in advance for your cooperation. Hour: Indicate your position in the scheme:
1. Which of the following option best indicate your clothing?
1. Shorts and short-sleeved shirt 2. Throusers and short-sleeved shirt 3. Throusers and long-sleeved shirt 4. Throusers and jersey 5. (3) + jacket 6. (3) + jersey and interior shirt 7. Knee-length skirt and short-sleeved shirt 8. Knee-length skirt and long-sleeved shirt 9. Knee-length skirt and jersey 10. (7) + jersey 11. (7) + jacket 12. Ankle-length skirt, long-sleeved shirt and jacket
2. How do you asses your thermal sensation? o Hot (+3) o Warm (+2) o Slightly warm (+1) o Neutral (0) o Slightly cool (-1) o Cool (-2) o Cold (-3)
3. How do you perceive the room in the air? o Wet o Slightly wet o Neutral o Slightly dry o Very dry
o Laden air o Slightly laden air o Fresh
4. How do you perceive the air movement in the room? o Very low o Slightly low o Neutral o Slightly high o Very high
5. How do you perceive the illumination level of the room? o Very intense o Slightly intense o Neutral o Slightly dim o Very dim
97
Annex 2
Description and thermal characteristics of the sports hall construction elements implemented in the
TRNSYS simulation.
Table 49. Exterior façades composition
Façades
NE and SW From the inside to the outside Conductivity
(kJ/hmK)
Heat Capacity
(kJ/kgK)
Density
(kg/m3)
Thickness
(mm) Layer
1 OSB panel 0.468 1.7 650 0.018
2 Fiberboard MDF - GUTEX 0.252 1.7 250 0.2
3 Larch wood 0.504 2.8 600 0.018
4 Air gap Resistance = 0.05 m2K/kJ 0.042
5 Ceramic 3.132 0.9 1250 0.04
Façades
SE and NW From the inside to the outside Conductivity
(kJ/hmK)
Heat Capacity
(kJ/kgK)
Density
(kg/m3)
Thickness
(mm) Layer
1 OSB panel 0.468 1.7 650 0.018
2 Fiberboard MDF - GUTEX 0.252 1.7 250 0.2
3 Larch wood 0.504 2.8 600 0.04
4 Air gap Resistance = 0.05 m2K/kJ 0.02
5 Euromodul 44 – Metal profile 180 0.5 7800 0.001
Table 50. Partition (interior) wall composition
Partition wall
NW From the inside to the outside Conductivity
(kJ/hmK)
Heat
Capacity
(kJ/kgK)
Density
(kg/m3)
Thickness
(mm) Layer
1 OSB panel 0.468 1.7 650 0.018
2 Fiberboard MDF - GUTEX 0.252 1.7 250 0.2
3 Larch wood 0.504 2.8 600 0.018
Table 51. Roof composition
Roof From the inside to the outside
Conductivity
(kJ/hmK)
Heat
Capacity
(kJ/kgK)
Density
(kg/m3)
Thickness
(mm) Layer
1 Fiberboard MDF - Acoustic 0.504 1.7 600 0.025
2 OSB panel 0.468 1.7 650 0.015
3 Fiberboard MDF - GUTEX 0.252 1.7 250 0.2
4 OSB panel 0.468 1.7 650 0.015
5 Air gap Resistance = 0.05 m2K/kJ 0.05
6 Euromodul 44 – Metal profile 180 0.5 7800 0.001
98
Table 52. Ground floor composition
Ground floor From the inside to the outside
Conductivity
(kJ/hmK)
Heat
Capacity
(kJ/kgK)
Density
(kg/m3)
Thickness
(mm) Layer
1 Concrete 4.86 1 2000 0.2
2 Wood - Parquet 0.756 2.8 800 0.004
3 Plywood panel 0.324 1.6 300 0.01
4 Plywood panel 0.324 1.6 300 0.012
5 Polyethylene 1.188 2.2 920 0.01
6 Linoleum 0.36 1.4 270 0.012
Table 53. Windows characteristics
g
Heat gain
coefficient
T-sol
Solar
transmittance
Rf-sol
Solar direct
transmittance
T-vis
Visible
transmittance
Window 1_lower level 0.368 0.296 0.2 0.496
Window 2_higher level 0.335 0.294 0.325 0.388
Window 3_skylight 0.589 0.426 0.266 0.706
99
Annex 3
100
Annex 4
101
Annex 5
Table 54. PV monthly shading losses (%). Skelion calculation
PV configuration Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 0.09 0.08 0.08 0.04 0.02 0.03 0.04 0.01 0.06 0.04 0.07 0.08
2 1.82 2.25 1 0.59 0.34 0.43 0.59 0.55 1.14 1.34 3.15 3.84
3 0.06 0.03 0.04 0.04 0.05 0.06 0.07 0.05 0.06 0.08 0.06 0.07
4 0.13 0.17 0.21 0.21 0.24 0.23 0.27 0.25 0.2 0.19 0.13 0.16
5 0.08 0.1 0.07 0.07 0.12 0.12 0.15 0.13 0.09 0.05 0.05 0.11
6 0.1 2.04 0.39 0.41 0.04 0.02 0.03 0.2 0.33 1.36 1.71 3.87
7 0.21 0.33 0.32 0.31 0.48 0.44 0.51 0.37 0.32 0.43 0.45 0.32
8 4.57 2.48 1.27 0.24 0.18 0.00 0.06 0.34 1.21 2.25 4.57 4.66
9 1.45 1.06 0.47 0.21 0.13 0.12 0.16 0.21 0.47 0.67 1.94 1.61
10 0.06 0.08 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.07 0.05
11 0.19 0.32 0.13 0.00 0.00 0.00 0.00 0.02 0.00 0.3 0.3 0.64
12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
14 2.61 6.13 9.05 17.8 16.8 19.49 22.11 20.04 15.31 5.07 2.01 1.82
15 2.62 6.13 11.6 15.95 16.8 19.49 22.11 18.12 12.01 7.23 2.02 1.85
16 0.90 2.15 3.92 5.32 5.60 6.50 7.37 6.05 4.02 2.47 0.73 0.74
